Latest AI and machine learning research in ethics for healthcare professionals.
Quantitation of structures is a critical step in analyzing images. Automated segmentation of biological samples remains a central challenge in microscopy, where variations in signal/noise, intensity, texture, and edges hinder accurate delineation of cellular and tissue structures. Adaptations of foundation models such as Segment Anything Model (SAM) remain computationally intensive and require lar...
Enzymes present a sustainable alternative to traditional chemical industries, drug synthesis, and bioremediation applications. Because catalytic residues are the key amino acids that drive enzyme function, their accurate prediction facilitates enzyme function prediction. Sequence similarity-based approaches such as BLAST are fast but require previously annotated homologs. Machine learning approach...
Over the past sixty years, evidence accumulation models have emerged as a dominant framework for explaining the neural and behavioral aspects of the p...
Antibody discovery remains constrained by resource-intensive experimental screening approaches that offer limited control over critical properties. He...
Cognitive conflict is a ubiquitous aspect of our daily life, yet its underlying neural mechanisms remain debated. Competing theories propose that conf...
Recent advances in high-throughput single-cell technologies have enabled characterization of cellular states across distinct omics layers, yielding co...
Despite their potential, patient-reported outcomes (PROs) are often underutilized in clinical decision-making, especially when improvements in PROs do...
Ensuring privacy in distributed machine learning while computing the Area Under the Curve (AUC) is a significant challenge because pooling sensitive t...
Digital pathology has significantly advanced cancer diagnosis by enabling high-resolution visualisation and assessment of tissue specimens. However, t...
Magnetic Resonance Spectroscopic Imaging (MRSI) enables non-invasive mapping of brain metabolite concentrations but remains computationally intensive ...
Artificial Intelligence (AI) is being designed, tested, and in many cases actively employed in almost every aspect of healthcare from primary care to ...
South African young adults are at increased risk for HIV acquisition and other non-communicable diseases and face significant barriers to accessing he...
While associations of antibiotic resistance traits are not random in multidrug-resistant (MDR) bacteria, clinically relevant resistance patterns remai...
Despite CBT’s status as a first-line treatment, a substantial proportion of patients does not experience sufficient symptom relief. Recent advances in...
Artificial Intelligence (AI)-based prediction models, including risk scoring systems and decision support systems, are increasingly adopted in healthc...
Large language models’ (LLMs) alignment with ethical standards is unclear. We tested whether LLMs shift medical ethical decisions when given socio-dem...
Anemia, or low blood hemoglobin (Hb), affects one third of the world population, and is particularly prevalent in women and children in lower resource...
Robust de-identification is necessary to preserve patient confidentiality and maintain public acceptance of electronic health record (EHR) research. M...
The use of Artificial Intelligence (AI) methods in palliative care research is increasing. Most AI palliative care research involves the use of routin...
The Mahidol Oxford Tropical Medicine Research Unit (MORU), headquartered in Bangkok, conducts research on tropical medicine and global health. MORU wo...