Latest AI and machine learning research in prescriptions for healthcare professionals.
Drug discovery is a complex and multifaceted process aimed at identifying new therapeutic compounds ...
Inductive bias in machine learning (ML) is the set of assumptions describing how a model makes predi...
BACKGROUND: In older adults with hypertension, hip fractures accompanied by preoperative acute heart...
BACKGROUND: Antibodies play a crucial role in disease treatment, leveraging their ability to selecti...
Novel drug-target interaction (DTI) prediction is crucial in drug discovery and repositioning. Recen...
Reporting of diagnostic nuclear images in clinical cancer management is generally qualitative. Thera...
Patients with end-stage kidney disease (ESKD) frequently experience anemia, and maintaining hemoglob...
Materials data science and machine learning (ML) are pivotal in advancing cancer treatment strategie...
Existing deep learning methods have shown outstanding performance in predicting drug-target interact...
Human interaction recognition (HIR) between two people in videos is a critical field in computer vis...
Diabetes management is often complicated by comorbidities, requiring complex medication regimens tha...
Skin diseases are a significant global public health concern, affecting 21-85% of the world's popula...
Alzheimer's disease (AD), a prevalent neurodegenerative disorder, presents significant challenges in...
The Co-administration of multiple drugs can enhance the efficacy of disease treatment by reducing dr...
Differential game is an effective technique to describe the negotiation between the humans and robot...
This study addresses the challenges of human-robot interactions in real-time environments with adapt...
Facial expression recognition (FER) is significantly influenced by the cultural background (CB) of o...
As an early indicator of dementia, mild cognitive impairment (MCI) requires specialized treatment ac...
The purpose of this review is two-fold: (1) to summarize artificial intelligence and machine learnin...
BACKGROUND: Bioequivalence risk assessment as an extension of quality risk management lacks examples...
Identifying the frequencies of drug-side effects is crucial for assessing drug risk-benefit. However...