Precision Medicine

Researchers have used machine learning to predict wellbeing—not only objective physical condition but also subjective overall health—as a function of demographic, socioeconomic and geographic factors.

The aggregated datasets are so complex, applying algorithmic analysis for medical uses may help expand AI as it unlocks biology.

Johns Hopkins researchers have used deep neural networks to draw important insights—prescriptive as well as descriptive—into adaptive immunity from massive stores of T-cell receptor sequencing data.

An AI system for diagnosing prostate cancer on biopsy slides has achieved 98%-plus performance in sensitivity, positive predictive value, specificity and negative predictive value.

Two healthcare heavyweights are combining forces to form a technology center they hope will, over the next 10 years, “fundamentally advance the pace” of discovery in medical science and healthcare innovation.

Noting that multiple sclerosis now affects more people between 50 and 60 than any other age group, researchers have shown how machine-learning gait analysis can help personalize therapy regimens.

Academic researchers in the U.K. have completed a systematic review of 62 representative studies on the use of AI for COVID-19 diagnostics and prognostics on X-rays and CT scans. Their findings may strike some as a setback.  

The demand for tailored PHI consent for research is strongest among adults 49 and younger, pressing the need to speed the evolution of policies conducive to AI development.

The FDA has granted 510(k) clearance to clinical decision support software that uses AI to detect small but potentially cancerous lesions in the lungs.

Researchers have demonstrated that deep learning models can help neurologists interpret epileptic episodes during and between seizures from relatively few scalp electroencephalography (EEG) readings.

Researchers have developed an AI-based system that can direct the administering of iron and other red-blood-cell stimulators nearly as well as experienced physicians.

The European Union has granted CE mark approval to a U.S.-based maker of AI software that aids radiologists in distinguishing between benign and malignant lesions on breast ultrasound images.