The most common reason people skip hearing aids is not cost. It is that they never get tested in the first place. Samsung is betting that a pair of earbuds many people already own can close part of that gap.

The company says the Galaxy Buds 3 Pro and Galaxy Buds 4 Pro will soon work as hearing aids, with the feature rolling out in early 2027. South Korea’s Ministry of Food and Drug Safety (MFDS) has now approved the software as a digital medical device. That follows an earlier approval from the US FDA this year.

Two features are involved. Hearing Check is a hearing test, and Hearing Care is the amplification function. Both live in the Galaxy Buds settings menu on a connected Galaxy smartphone, so there is no separate app or device to buy.

The test method matters here. Samsung says it is built on pure-tone air conduction audiometry, a clinical standard. The earbuds play tones at different frequencies and find the quietest sound the user can hear in each ear. The system then produces a personalized audiogram and sorts hearing ability into six levels. Based on the result, users get recommendations and follow-up guidance suited to their severity.

The amplification side uses NAL-NL2, a prescription formula developed by Australia’s National Acoustical Laboratories and widely used in clinical fitting. The earbuds calculate the right amount of gain for each frequency band and boost only the sounds the wearer struggles to hear. That is different from simply turning up the volume, which can make everything louder and more fatiguing without improving clarity.

Hearing Care is intended for adults aged 18 and older who suspect mild-to-moderate hearing loss. Users can set up their own hearing assistance without visiting an audiologist. That limit is important. People with severe or sudden hearing loss still need a clinical evaluation, and the built-in guidance is meant to point them in that direction.

The bigger picture is a shift in how hearing care is delivered. In the US, the FDA created an over-the-counter hearing aid category in 2022 to lower barriers for adults with mild-to-moderate loss. Apple brought a similar capability to AirPods Pro, and other consumer audio makers have been moving the same way. Samsung’s approvals put it firmly in that group, and the MFDS clearance extends its reach beyond the US market.

For clinicians, the appeal is early detection. Untreated hearing loss is linked to social isolation and cognitive decline, yet many people wait years before seeking help. A test that takes a few minutes on hardware people already wear could bring more patients into the system sooner. Whether those results translate into proper follow-up is the open question.

Consumer earbuds will not replace custom-fitted devices for people with more complex needs. But for the large group with mild loss who would never book an appointment, a familiar product with clinical-standard methods behind it is a practical option. We will learn more once the rollout begins in early 2027.

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Plenty of companies announce AI health partnerships. Few pick a whole country as the proving ground. Google’s latest announcement at its Google for Health Summit in Singapore does exactly that, pairing a new local research hub with deployments inside the city-state’s public healthcare institutions.

The company says the goals are to speed up scientific discovery, support frontline clinicians and give residents better tools to manage their own health. Most of the detail is early-stage, and none of it comes with outcome data yet. But the structure of the program is worth watching.

A research hub with local roots

Google Research is setting up a Singapore hub staffed by research scientists and software engineers. Its focus is foundational AI models, and it will work with the National University of Singapore and Nanyang Technological University on research support and talent development.

The company will also expand existing health research in the country. That includes bringing open models such as MedGemma into frontline care settings. Because the models are open, hospitals can build customized tools while keeping full control of their data. Data sovereignty is a recurring theme here, and for good reason. Health systems are wary of sending patient information beyond their own walls.

On the funding side, Google.org and Google DeepMind are contributing $7 million to the Philanthropy Asia Alliance’s Health for Human Potential Coalition. Of that, $1 million goes to PathGen, an AI platform that helps countries detect disease threats sooner and share data for public health intelligence, again without moving data out of the country.

Two clinical tests

The most concrete work involves clinicians and patients. Google DeepMind is working with the National University Health System to evaluate an AI co-clinician tool. It helps doctors synthesize medical guidelines and literature and answers clinical queries while they care for patients. Note the word evaluate. This is an assessment, not a rollout, and the results will matter more than the announcement.

Separately, Google Cloud is partnering with NHG Health on a population health program. AI-driven predictive models forecast risks such as chronic conditions across sub-populations. Those forecasts feed an AI health coach inside the NHG HealthBot, built on Google’s Gemini Enterprise for Customer Experience platform. Residents receive personalized lifestyle guidance and preventive care reminders.

Why it matters

Singapore, like many countries, faces an aging population and pressure to shift from treating illness to preventing it. Prediction tools that flag risk early, paired with a coach that nudges behavior, fit that need neatly. Whether they change outcomes is the open question.

Google itself acknowledges that technology is only part of the answer. Health systems also have to integrate AI responsibly, govern it safely and turn it into human-centered care. That is the right caveat. Clinical decision support tools have a long record of working in demos and stalling in workflow.

Singapore is a sensible place to test this. It has a centralized public system, strong academic partners and clear data rules. If the co-clinician and population health pilots produce credible evidence, other countries will have a template. If they don’t, that will be informative too.

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Most interventional suite upgrades are sold on image quality. GE HealthCare is pitching Allia Celeo on something harder to measure: how many small interruptions a team faces over a day. The company introduced the ceiling-mounted image guiding system at TCT 2026 in San Diego, aimed at busy labs that handle many kinds of cases.

That framing makes sense. In high-volume cath labs and interventional radiology suites, lost minutes come from repositioning, awkward sightlines, dose adjustments and unexpected equipment faults, not just from the procedure itself. Allia Celeo is built to trim each of those.

Hardware built around space and access

The system has a slim, symmetrical ceiling gantry with integrated cabling, which frees floor space for staff and equipment. Its extra-wide bore lets the C-arm rotate around the patient and reach steep angulations, including in patients with a high BMI. That matters, because larger patients are a routine challenge for imaging geometry rather than an edge case.

A slim C-arm and thin detector lift are meant to keep sightlines open across the table. Fast ceiling panning and extended table coverage support head-to-toe imaging. A feature called InnovaBreeze moves the table and gantry automatically to assess the full lower-limb anatomy in one acquisition, which is relevant for peripheral vascular work.

Clinicians can adjust gantry and table positions from several locations. An on-screen digital twin is designed to help with positioning, and controls and layouts can be personalized.

AI in the image chain

The image chain automatically adjusts acquisition parameters, aiming for consistent quality at the lowest dose. Advanced rendering offers one-click access to cardiac image renderings matched to each operator’s preference. Dose management in the background is a practical gain, if it performs as described. GE has not published clinical data with this announcement, so that remains a claim to test in real suites.

Compatibility across specialties

The company lists a wide set of compatible tools:

• Coronary and structural heart: StentViz, 3DStent, Valve ASSIST 2, and the Mac-Lab hemodynamic system with integrated FFR and dPR indexes
• Interventional radiology and oncology: Embo ASSIST AI, Vessel ASSIST and Needle ASSIST for embolization planning, 3D roadmapping and needle guidance
• Other integrations: Vscan Air handheld ultrasound and compatible third-party intravascular imaging and physiology systems

Applications are sold separately, and 3DStent requires a 30-cm detector.

Uptime as a clinical issue

Allia Celeo is designed to work with OnWatch Predict, which combines 24/7 remote monitoring with deep learning analytics to anticipate unplanned downtime. A cancelled case list affects patients and staff, so predictive service is a real part of throughput. Still, buyers should ask for uptime figures from existing installations.

Where it fits and what is missing

This is the second new Allia system in under a year, after the floor-mounted Allia Moveo, which was unveiled in 2025 and launched commercially earlier this year. GE is also offering an upgrade program for existing customers. The strategy is clear: give hospitals different room configurations on one platform.

One caveat matters for US readers. Allia Celeo is CE marked, but its 510(k) is pending with the FDA and it cannot be sold in the United States yet. Availability may also vary elsewhere. Until independent performance data appear, the system’s promise rests on design intent. Interested attendees can find GE HealthCare at booth #5237.

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Patients are already pasting lab results into chatbots. The question has never really been whether they will ask AI about their health, but whether the AI will see anything more than a screenshot and a guess. athenahealth is betting that a direct, patient-authorized connection to the actual record is a better answer.

On November 2, 2026, the company announced athenaPatient MCP, a server that lets patients connect their athenahealth records to Anthropic’s Claude. It is available starting today.

Why patients are asking for this

The demand is easy to see. An August 2026 Pew Research Center survey found that 34% of U.S. adults have used AI assistants for health purposes, from checking symptoms to making sense of a diagnosis. Most of that use happens with no access to the person’s real data. The answers tend to be generic, or they rest on whatever the patient remembers to type.

That gap matters clinically. A person who misreads a lab value or misremembers a medication dose can walk into an appointment with the wrong idea. Connecting the assistant to the source record is one way to narrow that risk, though it does not remove it.

How the connection works

The tool uses the Model Context Protocol, an open standard that gives AI models defined, secure points of access to structured data in authorized systems. The athenaPatient MCP server links Claude to athenahealth’s platform. When a patient asks, Claude can retrieve record information through a secure connection that requires sign-in with the patient’s athenahealth credentials.

Claude Pro and Max users in the U.S. can add the connector in their Claude settings. After that, they can ask questions in plain language. Claude can reference the following data:

• Lab results and diagnostic reports
• Vitals
• Medications and allergies
• Health conditions and procedures
• Immunizations
• Visit history
• Care plans

The company says patients choose which information to make available and can revoke access at any time. Pricing for the connector itself was not disclosed. Access depends on a paid Claude plan.

What the companies say

Paul Brient, athenahealth’s chief product and operations officer, called the launch “an important milestone in responsibly integrating AI into the patient experience,” and said the goal is to help patients get value from their own data. Syed Mohiuddin, Anthropic’s head of healthcare, pointed to the questions that come up between visits, such as what a result means or what to ask next time. The aim, he said, is to help patients feel “more confident and prepared” when they talk with their care team.

That framing is worth noting. Neither company is pitching this as a replacement for clinical judgment. It is positioned as preparation for the visit, not a substitute for it.

What clinicians and entrepreneurs should watch

For clinicians, the practical effect may be patients who arrive with sharper, more specific questions. That can be useful. It could also mean more portal messages and more time spent correcting an AI’s misreading of a result. The release offers no data on accuracy, error rates, or how Claude handles ambiguous findings, and those details will matter.

The release also leaves open how patient data is treated once it reaches the AI provider. Patient-directed access to records is generally not governed the way a provider’s own systems are, so the consent and revocation controls carry real weight. Patients should read the terms before connecting.

For health entrepreneurs, the signal is the architecture. An EHR vendor is exposing patient data through a standard connector rather than building its own chatbot. If that approach spreads, interoperability work may shift toward making records easy for any AI tool to consume, with the patient holding the keys.

athenahealth calls this launch “just the beginning” and describes it as a step toward patients using AI to understand their records and prepare for care decisions. Whether it improves understanding or simply adds a new source of confident-sounding errors will depend on evidence the companies have yet to publish.

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Shortness of breath is one of the hardest symptoms to sort out at the bedside. Heart, lungs, or both? GE HealthCare is betting that AI built into a pocket-sized ultrasound can help clinicians answer that faster, and it has just added two tools to try to do it.

On November 3, 2026, the company announced Lung Guidance and AutoAS for its Vscan Air handheld system. Both are available only on the Vscan Air SL model. They join Caption AI, which guides cardiac scans, and Caption Interpretation Auto EF, which supports ejection fraction assessment.

What Lung Guidance does

Lung ultrasound is useful, but image quality depends heavily on the operator. Lung Guidance addresses that with real-time coaching. It directs users to the right anatomical landmarks in each zone of the standard 8-zone protocol, detecting structures such as the pleural line, A-lines, rib shadows, the diaphragm and the abdomen.

When landmark and image-quality criteria are met, AutoCapture records a clip automatically. If those conditions are not reached, a Save Best Clip feature keeps the best image from each view. The tool also detects and scores B-lines and generates a report to organize findings.

In validation testing, non-expert users acquired diagnostic-quality exams 95.2 percent of the time, compared with 96.8 percent for experts. GE describes this as a descriptive assessment, so it is not a head-to-head trial with formal statistical comparison. Still, a gap of 1.6 points is small.

What AutoAS does

AutoAS looks for moderate-to-severe aortic stenosis. It analyzes standard 2D cardiac images from at least two compatible views: parasternal long-axis, parasternal short-axis at the aortic valve, or apical five-chamber. It then gives an estimate of whether findings suggest moderate-to-severe AS, along with a confidence score.

GE says the algorithm was trained and validated against a reference panel of expert cardiologists, and that it can reduce the variability of missed AS compared with visual interpretation alone. The company has not published specific performance figures in this announcement. The tool is labeled a diagnostic aid, not a standalone diagnosis, and final decisions stay with the clinician and formal echocardiography.

Why it matters

Aortic stenosis is often underrecognized, and access to formal echo can lag, particularly outside large centers. A screening-style flag at the first encounter could prompt earlier referral. That is the realistic ambition here: not replacing the echo lab, but shortening the wait before someone gets there.

The broader trend is clear. Point-of-care ultrasound is spreading to more users, including those with limited training, and AI guidance is the main way vendors are trying to keep quality acceptable. Clinicians evaluating these tools should ask for independent data, especially on how AutoAS performs across patient populations and in the hands of novices.

Availability

Both tools are FDA 510(k) cleared and CE marked. They are sold through Vscan Air Innovation Packages in the United States and select countries. Existing customers with a valid Innovation Package subscription or license should receive the updates by the end of November 2026. Offerings vary by location and system model.

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A ring is easier to sleep in than a watch. That simple fact is why Samsung’s latest move matters: the best screening tool is the one people actually wear through the night.

Samsung says its updated Sleep Apnea feature is now available on Galaxy Ring and Galaxy Watch, and that it is the first company to offer sleep apnea risk detection on a smart ring. The update has US FDA clearance from July 2026 and approval from Korea’s Ministry of Food and Drug Safety (MFDS). The original feature received FDA De Novo authorization in February 2024, the first for a wearable designed to detect signs of moderate to severe sleep apnea.

What has changed

The new algorithm analyzes vitals during sleep in more depth. It also reports the level of breathing disruption detected, rather than only flagging risk. For clinicians, that could make the conversation with a patient more concrete, though Samsung has not published performance data for the update in this announcement.

The feature runs in the Samsung Health Monitor app. It needs just two nights of valid data within a 10-day window, a low bar that should suit people who won’t commit to weeks of tracking.

Who it is for, and who it is not

This is an over-the-counter, software-only medical application. It is meant for adults 18 and older and for on-demand use. It is not for people already diagnosed with sleep apnea, and it does not replace diagnosis or treatment by a clinician.

On the watch side, it is available on Galaxy Watch 9 with Wear OS 7.0 or higher. Support for Watch 7 and 8 is coming through software updates.

Why it matters

Sleep apnea is widely underdiagnosed, and formal sleep studies are inconvenient and costly. Consumer wearables with regulatory backing can act as a first filter, pushing people toward testing who might otherwise never ask. The caveat is familiar: screening tools can raise false alarms and miss cases, so clinical follow-up still matters.

Samsung says it will expand availability to more countries. Regulatory approval market by market will determine how fast that happens, and whether rings can match watches in real-world accuracy is the question clinicians should watch.

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A yes-or-no answer is not much use to someone who snores through the night and wonders whether it matters. Samsung seems to agree. Its updated Sleep Apnea Detection feature no longer just flags signs of the condition. It sorts them into levels of severity, and that is a more useful thing to hand a patient.

The upgrade is coming to the Galaxy Ring and to recent Galaxy Watch models. South Korea gets it first, because the feature has been approved by the country’s Ministry of Food and Drug Safety (MFDS).

How the new grading works

The earlier version looked for the presence or absence of sleep apnea signs. The new one uses AI to analyze breathing data and categorizes disturbances during sleep as mild, occasional, or frequent.

Getting a result takes some commitment. Users need to record at least five hours of sleep on two separate nights within a 10-day period, using the Samsung Health Monitor app. That is a reasonable bar. Short or fragmented recordings would make any breathing analysis less reliable.

Which devices get it, and when

The first wave arrives in South Korea in November. It covers the Galaxy Ring, the Galaxy Watch 9, and the Galaxy Watch Ultra 2. Support will later extend to the Galaxy Watch 7, Galaxy Watch Ultra, Galaxy Watch 8, and Galaxy Watch 8 Classic.

Older models are left out. They will keep the previous version of Sleep Apnea Detection. Samsung has not given dates for markets outside South Korea, so users elsewhere will have to wait for regional approvals.

Why it matters clinically

Sleep apnea is widely underdiagnosed, and it is often linked to hypertension and stroke. Many people never get tested because the standard route, an overnight sleep study, is inconvenient and sometimes hard to access. A wearable that spots warning signs at home can push more people toward that first conversation with a doctor.

Severity grading could help here. A person told they have frequent disturbances has a clearer reason to seek an evaluation than someone who receives a vague alert. And a clinician looking at a patient’s data would at least have a rough sense of how often breathing is being interrupted.

Samsung is careful about positioning. It calls the feature a preventive wellness monitoring tool for adults, meant to help catch early signs, and says it is not a replacement for a professional medical diagnosis. That framing is correct. Consumer wearables can screen and prompt, but they cannot confirm. Sleep apnea still needs clinical assessment.

The bigger picture

Wearable makers are moving from general wellness tracking toward features that need regulatory sign-off. The MFDS approval is a good example. It gives the feature credibility that a simple app update would not carry, and it sets a pattern other markets are likely to follow.

Including the Galaxy Ring matters too. Many people find a ring more comfortable to wear overnight than a watch, and comfort affects whether anyone actually collects five hours of data. If more people wear the device to bed, more people get screened.

The real test will come after launch. Accuracy data, the rate of false alarms, and how many users go on to seek a diagnosis will show whether graded results change behavior or just add another number to a health app.

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Most people who start a GLP-1 drug stop taking it. Only 32% remain on therapy at the end of year one, and just 15% by year two. Counsel Health thinks the missing piece is continuous medical support, and it just built a program around that idea.

The New York company, which describes itself as AI-native primary care, announced a weight management program on October 27, 2026. It is available directly through Counsel and through LillyDirect, Eli Lilly’s direct-to-consumer digital pharmacy.

Why the timing matters

GLP-1 use is climbing fast. About 11% of U.S. adults now take these drugs for weight loss, up from 3% in 2024. More patients means more questions about side effects, dosing, and progress, often with little follow-up once the prescription is written.

What members get

Members can reach board-certified physicians on demand, typically within minutes. The membership also covers primary care, including urgent concerns and related conditions such as hypertension, diabetes, and high cholesterol. That bundling makes clinical sense, since obesity rarely travels alone.

Counsel says its AI-supported model keeps costs below traditional weight management programs. Pricing comes as an annual membership or a pay-as-you-go option. The company’s medical AI is free to use and routes people to a physician when needed.

“GLP-1s are powerful medications, but a prescription alone is not a care model,” said Dr. Muthu Alagappan, Counsel’s founder and CEO.

The LillyDirect connection

Through LillyDirect, Counsel is one of the listed providers. Eligible consumers who choose it receive a physician-led evaluation, a GLP-1 prescription when clinically appropriate, and ongoing support. The program is available in the 44 states where Counsel’s consumer platform operates.

What to watch

The announcement offers no outcome data. Whether this model improves the 32% retention figure is the real question, and Counsel has not yet shown that it does. Still, the pitch is sound: pair access to a drug with access to a doctor. If it works at a lower price, it could pressure telehealth competitors that treat the prescription as the endpoint.

More information is available at counselhealth.com.

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The best CGM might be the one you forget you have. Senseonics is betting on that idea with Freedom, an implantable glucose sensor that talks directly to a phone, with nothing stuck to the skin.

The company has started its first-in-human study of the investigational device. Freedom uses the same sensing technology as Eversense 365, the one-year implantable CGM. The change is an integrated battery and built-in Bluetooth, which removes the external transmitter that Eversense users currently wear over the sensor.

What the study will and won’t tell us

This is an early feasibility study. Its job is to check safety and basic device function, including whether the sensor’s direct Bluetooth link works in people. It is not an accuracy trial. Senseonics says it plans a pivotal study in 2027 and is aiming for a commercial launch in 2028. Those dates depend on clean data and FDA review, so treat them as targets.

The preclinical groundwork

In the second quarter of 2026, the company tested several Bluetooth Low Energy antenna designs and implant locations. Over about seven weeks and more than 18,500 communication data points, the preferred design reached 100% communication success within the target distance. That is encouraging. But preclinical results don’t always carry over to human tissue, movement and daily life, which is why this first human data matters.

Why it matters

Eversense 365 is the only one-year CGM, and it already reduces the sensor changes that burden users of 10- to 15-day devices. Still, the removable transmitter is a wearable that needs charging and placement. Removing it would address a common complaint about device visibility and daily upkeep.

There are open questions. A battery inside the implant raises long-term performance and safety questions that the pivotal trial will need to answer. Clinicians will also want to see accuracy over a full year without an external component, and how users receive alerts and manage insertion and removal.

Senseonics CEO Tim Goodnow said the company is leading the race to make CGM invisible. That claim will be tested by the data. For now, Freedom is a credible next step built on a sensor that is already on the market, which lowers some development risk, though not all of it.

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Most people get their cholesterol checked once a year and weigh themselves most mornings. The two data sets almost never meet. A new partnership between Withings and Function tries to fix that, and the approach is simple enough to be useful.

Announced on October 22, 2026, the integration connects Withings’ connected devices with Function’s lab testing platform. Data flows in both directions, so neither company’s users have to export spreadsheets or carry screenshots to an appointment.

What the integration does

Function members can sync daily readings from Withings devices, including body composition and blood pressure, directly into the Function app. That gives periodic lab results a continuous backdrop. A single LDL number means more when you can see what weight and blood pressure did in the months around it.

The reverse also works. Results from Function’s 160+ lab tests, which cover heart health, hormones, thyroid, nutrients and more, sync into the Withings app. There they sit next to the activity, sleep and cardiovascular data Withings users already collect.

The companies offer an example. A woman in her mid-forties notices disrupted sleep and a shifting body composition, though her routine hasn’t changed. Those signals are ambiguous alone. Hormonal? Metabolic? Something to raise with her doctor? With trends from her Withings devices and labs such as LDL cholesterol, HbA1c, ferritin and TSH in one view, she can bring numbers to the appointment instead of a list of symptoms.

Pricing and availability

The integration is live now in the U.S. Both companies attached offers to the launch:

• Withings users get a $30 credit toward a Function subscription, applied automatically through a dedicated Function section in the Withings app.
• Function members get 10% off Withings products, available through the Function app.

Function membership costs $365 per year, about $1 a day, and includes access to the 160+ lab tests, including biannual testing. MRI and CT scans are available at extra cost. Details on getting started are at withings.com/en-us/pages/withings-function.

Why it matters clinically

Withings has more than 15 million users worldwide and has built its reputation on clinical-grade home measurement. Function has pushed direct-to-consumer lab testing toward a subscription model with a layer of interpretation on top, which it calls Medical Intelligence. Put them together and you get something closer to a longitudinal record than either offers alone.

The timing makes sense. Many people are managing weight, metabolic health or cardiovascular risk, and a growing group is tracking changes while taking GLP-1 medications. For them, a scale reading and a lab panel answer different questions. Weight tells you the direction. Labs can show whether nutrients, glucose control or lipids are moving with it.

Eric Carreel, Withings’ chairman and co-founder, framed it as a story told over time rather than a moment. Jonathan Swerdlin, Function’s CEO, said health information should live in one place. Both are marketing lines, but the underlying point holds. Clinicians often struggle with fragmented data, and patients who arrive with organized trends tend to have more productive visits.

What to watch

The announcement doesn’t say how the combined data will be interpreted, or whether Function’s Medical Intelligence will draw conclusions from Withings measurements. That matters. Consumer devices and lab results come with different error margins, and a dashboard that implies correlation can mislead as easily as it informs. Clinicians will reasonably want to know how insights are generated and how they’re framed for patients.

Privacy is another open question, since two companies are now exchanging sensitive data. Neither company addressed it in the release.

Still, the direction is right. Connecting what people measure daily with what labs reveal periodically is a practical step toward more informed conversations between patients and doctors. Whether it improves outcomes is something only real-world use will show.

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