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A researcher who expected the evidence base to be thin says even she was surprised by how thin. Most cleared devices never appear in a registered clinical trial at all.
A new discussion paper proposes a two-axis risk framework and a physician-training analogy for evaluating generative AI devices. It is not a rule, and the agency is asking what one should look like.
The Aletta still needs a trained supervisor in the room, but it locates the vein, inserts the needle and fills the tubes on its own — and one person can now watch three of them at once.
Emulating a trial inside Veterans Health Administration records, researchers estimated adjusted mortality risk ratios of 0.90 to 0.84 for starting continuous glucose monitoring in older-onset type 1 diabetes.
It found no meaningful difference at six weeks. It enrolled 64 people, tested one device, and ran for six weeks. That is the entire head-to-head evidence base three years after the category opened.
A new structured dataset finally makes the approvals countable. Two trials published weeks apart show why counting them says little: 0.86 fewer migraine days in one, a 20-point symptom shift in the other.
The agency granted its first authorization for a software-aided adjunctive diagnostic device in wound assessment, a category built for tools that analyze a wound optically.
It is a medical-device biocompatibility standard, now built largely on lab-grown skin rather than animals. It measures whether a material irritates. It says nothing about whether a product works.
A content analysis of every FDA cybersecurity safety communication from 2013 to 2025 finds a small corpus, rising over time, and 94% of the flagged vulnerabilities rated severe.
The clearance is the third in a growing family of machine-learning notification algorithms built to spot serious cardiac conditions from a routine 12-lead ECG, a test most patients already get.
A new audit of China's regulatory record finds a market concentrated in radiology, dominated by deep learning, and clustered in four cities. It also finds the approval curve flattening.
An 11,018-measurement study in 24 English intensive care units found false negative rates up to 35.3 percentage points higher in patients with darker skin tones. A neonatal study published two days later did not.
One agency asked how to measure AI devices after they are deployed. Another asked how to speed adoption up. The offices that would answer the first question are losing staff.
A systematic review of every AI device authorised from 1995 to June 2024 found 97% cleared through the 510(k) pathway, which does not require independent clinical data on performance or safety.
A census of 691 AI-enabled devices cleared through 2023 found demographic data missing almost everywhere, three summaries reporting patient outcomes, and 113 recalls driven mostly by software.