AM-IA brings together news, research papers and applications relating to artificial intelligence published around the world into a single feed — and makes them available in your European language at the click of a button.
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Researchers have published 1,000 X-rays of children in cardiac intensive care, annotated on a device-by-device basis, along with a tool that is already integrated in real time at Boston Children’s Hospital.
A study involving more than 40,000 patients shows that the choice of method for imputing missing data alters the list of patients identified, even when the AUROC remains the same.
Optimised for MRI saturation transfer imaging, the Movienet network enables the acquisition of four times less data whilst maintaining a correlation of 0.965 with the reference method.
Trained on 12,392 nights of polysomnography data, the model goes beyond the traditional stages of sleep and identifies a pattern of disturbed sleep associated with higher mortality.
Trained on haemodynamic simulations, a model identifies the narrowed artery and the severity of the stenosis by comparing the predicted and observed velocity curves in eight vessels.
The RT-DETR detector achieves 98.25 per cent accuracy per image on Gram-stained smears photographed using the Galaxy S23 Ultra. The authors call for further multicentre validation.
A test set comprising 300 resolved clinical cases evaluates simulated ‘consultation meetings’ between models. Structured reports outperform unstructured ones in 7 out of 8 pipelines, with GPT-5.6-Sol coming out on top.
By retraining a segmentation network using scans of patients with defibrillators, researchers have improved the delineation of 20 substructures of the heart despite metallic artefacts.
In the JAMA, researchers from Harvard analysed 2.5 years’ worth of OpenEvidence usage by 950,000 clinicians: more than half of the queries relate to the choice of treatment.
The London-based notified body, which specialises in medical software and AI, aims to reduce certification lead times, which currently range from 12 to 18 months. Headline is leading this Series B funding round.
An audit of 2,550 scripted conversations shows that all chatbots direct users to a helpline, but that their persistence in the face of refusals ranges from almost none to nearly ten follow-up attempts.
Conventional scoring systems fail to take into account the complexity of these molecules designed for targeted protein degradation. RetroTAC draws on real-world synthetic pathways and clearly distinguishes the good candidates from the bad.
At Texas Children’s Hospital, a consensus pipeline combining two language models identifies 18 treatment responses; experts validate 90.2 per cent of its decisions.
Published in *Nature*, the study uses AI to quantify brown adipose tissue across more than 101,000 PET scans and identifies a potential drug candidate, losartan, which has yet to be tested in humans.
Researchers treat therapeutic decision-making in oncology as a detective game: the agent must first gather the right information about the patient before recommending a treatment.
Each agent plays the role of a healthcare professional involved in the patient’s care pathway; together, they draw up and amend the prescription. Tested on MIMIC-IV, the system significantly reduces drug-drug interactions.
Published in *Nature Biomedical Engineering*, the method locates the intubation probe with an average error of 0.67 cm, compared with 4.30 cm for the original adult model.
Based on an analysis of 16,361 CT scans from 3,473 patients, CAP-DIR utilises contours, dose data, clinical notes and patient history to track anatomical changes throughout the course of treatment.
The model works on MRI scans of varying resolution and contrast, and provides an uncertainty estimate that serves as a quality control measure, thereby enabling the analysis of large hospital databases.
By combining YOLO detection, particle filtering and monocular depth estimation, researchers have identified 82 per cent of occlusions and estimated depth to within one centimetre.