Background: Adverse events (AEs) related to cancer treatment represent a valuable source of information that can be used to adjust therapy for individual patients. The NIH developed the Common Terminology Criteria for Adverse Events…
Continue Reading
Regular physical activity offers extensive health benefits, yet current consumer wearables struggle to accurately quantify these effects at an individualized level. Sensor performance often falls short due to susceptibility to interferences, nonstandardized validation, and…
Continue Reading
Congenital and acquired heart disease affects approximately 1% of children worldwide, and right ventricular (RV) dysfunction is a common and complex manifestation in conditions such as congenital heart disease, pulmonary hypertension, and prematurity. Accurate…
Continue Reading
Real-time prediction of short-term mortality risk in the intensive care unit (ICU) is often hampered by missing medical data. To address this, we developed RealMIP, an end-to-end framework leveraging generative model for the dynamic…
Continue Reading
Introduction to Firstsource’s ISG Recognition
Firstsource Solutions Limited, a prominent global business process management services provider within the RP-Sanjiv Goenka Group portfolio, has achieved significant industry recognition by being designated as a ‘Leader’ in Digital…
Continue Reading
This study introduces a machine learning framework to predict effective antiviral combinations for influenza A. It identifies Pimodivir with Epinephrine or L-Adrenaline as synergistic agents, confirmed by experiments demonstrating increased binding affinity and viral…
Continue Reading
Atrial fibrillation (AF) is the most common arrhythmia worldwide and is associated with significant morbidity and mortality. FibriCheck is a medical analysis platform that uses an end-to-end algorithm to detect AF based on photoplethysmography…
Continue Reading
We developed a deep learning model trained on over two million ultrasound images from 78,531 pregnancies from Australia, India, and the UK to estimate gestational age (GA) directly from any fetal ultrasound image, regardless…
Continue Reading
Accurately predicting surgical and transfusion needs in traumatic brain injury (TBI) patients remains challenging in emergency settings. We developed multiomics data fusion (MDF) models integrating clinical biomarkers, neural radiological imaging, and clinical text mining…
Continue Reading
Current AI approaches for cardiac diagnosis require condition-specific supervised learning with extensive labeled datasets, leading to fundamental scalability barriers. We developed an ECG-CLIP model, applying contrastive multimodal learning to enable zero-shot cardiac diagnosis from…
Continue Reading
