Medical AI brings together our reporting on machine learning for clinical and biomedical problems, from diagnosis and prognosis to medical image analysis and decision support. Because mistakes in this domain carry a human cost, we pay close attention to evaluation, calibration, uncertainty, and the gap between benchmark numbers and bedside reliability. Expect grounded explainers of recent research rather than uncritical product announcements.
A diabetes research team can predict whether a patient’s HbA1c will be controlled after a year, but a colleague asks a harder question. Which recorded characteristics actually drive the fitted decision rule, and how uncertain are those coefficients? A support…
Decorrelated Scores for Sparse Hinge Classification Read More »
It is the middle of a night shift in an intensive care unit. One patient has a full set of overnight labs and a running stream of vital signs. The patient in the next bed has demographics and diagnosis codes…
ETF-UML Fuses Incomplete ICU Data Without Joint Training Read More »
A volunteer lies in a scanner at one of the Human Connectome Project sites. A screen flashes a cue, and for the next ten seconds or so they tap fingers, listen to a story, or hold a picture of a…
ASFFNet Decodes Brain States From Shorter fMRI Windows Read More »
Imagine a head and neck surgeon standing over a planning screen with a patient whose lower jaw must come out because of a tumor. Two virtual plans sit side by side. Both restore the outline of the face. Both use…
OsteoOpt Plans Jaw Reconstruction Around Bone Union Read More »
Think of a patient lying in a cardiac MRI scanner with an irregular heartbeat. The standard cine protocol asks for repeated breath holds and stitches the picture together from many beats, so an irregular rhythm smears the very thing the…
LAPANet Tracks Heart Motion Without Reconstructing MRI Read More »
Picture a patient in their fifties who has felt a tight chest on the stairs for months. The angiogram is done, the dye has outlined every large artery, and the cardiologist reports that nothing is blocked. The patient goes home…
PUNCH Estimates Coronary Flow Reserve Without a Wire Read More »
Picture a neuroradiologist who opens two brain scans of the same patient, one from spring and one from today. The patient is being followed after treatment for a brain tumor, and the scanner was replaced over the summer. The lesion…
Routine Brain MRI Becomes Quantitative T1 and T2 Maps Read More »
A surgeon at a hospital near Dresden removes an inflamed appendix through three small incisions, and the laparoscope records every second. Those recordings could teach an AI system to judge how severe the inflammation is, a call that shapes antibiotics,…
FedSurg Challenge Tests Federated Learning on Surgical Video Read More »
A dermatologist looking at a high frequency ultrasound scan of skin can read the layers the way a geologist reads rock strata. There is the bright epidermis at the surface, a dark band beneath it that clinicians call the subepidermal…
Physics Guided Synthetic Ultrasound for Skin Segmentation Read More »
Medical image segmentation is the task of coloring in a scan, drawing a precise outline around every organ or lesion so that a clinician can measure it, track it over time, or plan around it. Done by hand it is…
G2RA-Net: Graph Slices Sharpen Medical Image Segmentation Read More »