The Lancet

When to and when not to use machine learning in risk prediction models

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
IEEE

A Deep Reinforcement Learning Path Planning Method for Urban Heavy-lift eVTOL Considering Motion Attitude Constraints

Abstract: Heavy-lift electric vertical take-off and landing aircraft (eVTOL) play a vital role in advancing the low-altitude economy by enabling the transportation of high payloads in dense urban ...
BMJ Open

Exploring the dimensions of role transition to clinical educator among master’s anaesthesia students in Iran: protocol for a sequential multimethod study (exploratory ...

Introduction The transition from clinical practice to an academic role presents a multifaceted challenge for anaesthesia master’s students in Iran, as it demands not only clinical expertise but also ...
The Lancet

Machine learning prediction of 1-year mortality in older patients with heart failure: a nationwide, multicenter, prospective cohort study

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...
IEEE

A Novel Multimodal Process Monitoring Method Based on Improved Just-in-Time Learning-Assisted Stacked Quality-Related Autoencoder

Abstract: The complex manufacturing processes are characterized by strong nonlinearity, high dynamics, and multimodality, which make it difficult to effectively monitor production safety and product ...
Reuters

Drugmakers turn to AI to speed trials, regulatory submissions

SAN FRANCISCO, Jan 26 (Reuters) - Artificial intelligence has yet to deliver on the most challenging aspect of drug development -- finding new molecules that lead to major medical advances -- but it ...