Latest AI and machine learning research in devices and vaccines for healthcare professionals.
Accurately distinguishing between epileptic seizures (ES) and nonepileptic seizures (NES) is a significant clinical challenge that typically requires resource-intensive inpatient video-EEG monitoring. Here, we developed a novel Multimodal Large Language Models (MLLMs)-based method for automated extraction of semiological features from videos of seizure events, and subsequently, classified the even...
Antibodies against the SARS-CoV-2 spike receptor-binding domain provided effective COVID-19 treatment until resistant variants emerged. GB-0669 is a half-life extended monoclonal antibody optimized using artificial intelligence, targeting the conserved spike S2 stem helix, a region with limited selective pressure from natural infection-or vaccine-induced antibody responses. Pre-clinical safety stu...
Standard list-learning tasks such as the Rey Auditory Verbal Learning Test (RAVLT) and the California Verbal Learning Test (CVLT) have underpinned mem...
Mucosal vaccines may reduce both infection and transmission by engaging local immunity, yet the immunological pathways they activate in humans remain ...
Cancer therapeutic response patterns may be fundamentally influenced by embryonic germ layer origin. Emerging evidence suggests mesoderm-derived malig...
Advances in clinical research methods are frequently published in biomedical journals, but identifying these articles remains challenging due to their...
Planning invasive treatment for medication-resistant epilepsy relies on qualitatively interpreting seizure recordings from intracranial EEG (iEEG) rec...
Point-of-care ultrasonography (POCUS) enables clinicians to obtain critical diagnostic information at the bedside especially in resource limited setti...
Differentiating malignant from inflammatory uptake on 18F-FDG PET/CT remains a major diagnostic challenge, as standardized uptake value (SUV) lacks sp...
Large language models (LLMs) have demonstrated remarkable capabilities in various natural language processing tasks, including text classification, in...
Large language models (LLMs) are rapidly entering clinical care, yet their definitionally probabilistic outputs have delivered a variety of grossly un...
Artificial intelligence and automation technologies are displacing millions of workers across industries in developed countries, while many developing...
Achieving high retention of people living with HIV (PLHIV) in care remains a challenge in Uganda, despite substantial progress towards UNAIDS 95-95-95...
Genetically determined developmental disorders (GDD) are rare, heterogeneous conditions for which clinical diagnosis increasingly depends on genomic v...
Thigh-worn accelerometry is becoming increasingly popular in large-scale cohort studies for quantifying movement behaviour. Gait characteristics are a...
The 2022 global outbreak of clade IIb mpox represented a turning point in public health’s handling of poxviruses. The primary vaccine available for pr...
The convergence of the COVID-19 pandemic and the substance use disorder (SUD) crisis has created a syndemic that places this vulnerable population at ...
To develop and evaluate an automatic patient review analyzer that applies advanced Natural Language Processing (NLP) and machine learning methods to i...
The concept of fairness has been extensively examined within the domains of Machine Learning and Artificial Intelligence more broadly. It remains, how...
Surgery is inherently associated with complications, making early detection the cornerstone of timely intervention and improved outcomes. Artificial i...