A new medical large language model (LLM) achieved over 91% accuracy in identifying female participants diagnosed with major depressive disorder after analyzing a short WhatsApp audio recording where ...
A new medical large language model (LLM) achieved over 91 percent accuracy in identifying female participants diagnosed with major depressive disorder after analyzing a short WhatsApp audio recording ...
Background Suicide rates have increased over the last couple of decades globally, particularly in the United States and among populations with lower economic status who present at safety-net ...
Abstract: As deep learning (DL) continues to advance, effective feature extraction from large-scale data remains crucial for enhancing model performance. To leverage the advantages of the frequency ...
Introduction: Optimizing fracturing parameters under multi-factor, complex conditions remains challenging in low-permeability reservoirs. Methods: We extract stage-aware construction-curve features, ...
On a scorching July afternoon in Shanghai, dozens of Chinese students hunch over tablet screens, engrossed in English, math and physics lessons. Algorithms track every keystroke, and the seconds spent ...
Abstract: In modern healthcare, predicting diseases and identifying their underlying causes are crucial areas of study. This paper proposes a novel feature selection method based on entropy scores and ...
Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. In contrast, data-driven methods do not rely on fixed models or ...
Flatiron Health presents two new pieces of research demonstrating the potential of AI to advance oncology research across multiple tumor types NEW YORK--(BUSINESS WIRE)--Flatiron Health today ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results