
Predicting mortality dynamics in cancer patients: A machine learning approach to pre-death events.
Machine learning predicts cancer patient mortality dynamics, revealing three clinical patterns and key lab parameters. ππ‘
Discover the newest research about AI innovations in π¦ Epidemiology.

Machine learning predicts cancer patient mortality dynamics, revealing three clinical patterns and key lab parameters. ππ‘

Lung lobe segmentation tools evaluated: TotalSegmentator excels, while data diversity enhances model accuracy. ππ«

Exploring poliomyelitis dynamics through fractional-order models and deep neural networks reveals critical insights into disease transmission. ππ¦
AI detects one-third of interval breast cancers missed during screening, potentially improving outcomes for patients. ππ‘

UHL, UHN, and Microsoft partner to advance AI in healthcare, aiming to improve patient care and streamline services. π€π»

AI detects fatty liver disease using chest X-rays, offering a cost-effective and accessible diagnostic method. π©»π‘

AI ECG-derived age predicts CABG outcomes: 44% older than chronological age, linked to higher comorbidities and mortality. πβ€οΈ

AI in healthcare shows promise but faces barriers like complexity and fragmented regulations. Collaboration is key for progress. π€π

Deep-learning algorithms enhance lung lesion detection in CT scans, improving image quality significantly. ππ©»

Deep learning predicts tumor response in large HCC: HTI shows 54.45% ORR vs. 21.65% for HAIC. ππ§¬