HIV/AIDS

Extracting Pulmonary Embolism Diagnoses from Radiology Impressions Using GPT-4o: A Large Language Model Evaluation Study

Pulmonary embolism (PE) is a critical condition requiring rapid diagnosis to reduce mortality. Extracting PE diagnoses from radiology reports manually is time-consuming, highlighting the need for automated solutions. Advances in natural language processing (NLP), especially transformer models like GPT-4o, offer promising tools to improve diagnostic accuracy and workflow efficiency in clinical sett...

Predicting Suicidality in people living with HIV in Uganda: A Machine Learning Approach

People living with HIV (PLWH) are more likely to experience suicidal thoughts and exhibit suicidal behavior than the general population. However, there are currently no effective methods of predicting who is likely to experience suicidal thoughts and behavior. Machine learning (ML) approaches can be leveraged to develop models that evaluate the complex etiology of suicidal behavior, facilitating t...

Unravelling the Complex Inflammatory Landscape of COVID-19 infection: A Pathway to Biomarkers Identification in Infection-Associated Delirium in the ICU

Delirium is a serious complication in patients with COVID-19-related acute respiratory distress syndrome (ARDS) admitted to the intensive care unit (I...

Evaluating biomedical feature fusion on machine learning’s predictability and interpretability of COVID-19 severity types

Accurately differentiating severe from non-severe COVID-19 clinical types is critical for the healthcare system to optimize workflow. Current techniqu...

Tuberculosis disease severity assessment using clinical variables and radiology enabled by artificial intelligence

Radiology can define tuberculosis (TB) severity and may guide duration of treatment, however the optimal radiological metric to use and which clinical...

Pulmonary tuberculosis prediction using CAD4TB artificial intelligence (computer-aided detection for tuberculosis) based on thoracic x-ray photos among Indonesian subjects in hospital

Tuberculosis remains a major global health concern, particularly in high-burden countries where early detection is essential but often limited by insu...

Artificial Intelligence-based Diagnosis of Kaposi Sarcoma using Photographs in Dark-skinned Patients

Advanced-stage disease at the time of diagnosis, with resultant high mortality, is among the most urgent issues for HIV-related Kaposi sarcoma (KS) in...

Predicting Bacterial Vaginosis Development using Artificial Neural Networks

Bacterial vaginosis (BV) is a dysbiosis of the vaginal microbiome, characterized by the depletion of protective Lactobacillus spp. and overgrowth of a...

Activation status of immune cells in the airway is a defining feature of severe fungal asthma

Airborne fungi are potent inducers of respiratory disease and cause the debilitating conditions severe asthma with fungal sensitisation (SAFS) and all...

Dissecting the genetic complexity of myalgic encephalomyelitis/chronic fatigue syndrome via deep learning-powered genome analysis

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex, heterogeneous, and systemic disease defined by a suite of symptoms, includin...

Measuring the growth of infectious disease modelling publications and their impact on policymaking: a Large Language Model-assisted bibliometric review

Infectious disease modelling (IDM) is increasingly being used to understand disease transmission and inform public health policy. However, its growth ...

Deep learning-based localization of bounded edentulous spaces in intraoral occlusal images

This study developed a deep learning pipeline to localize bounded edentulous spaces with missing teeth FDI number directly from intraoral photographs,...

Multicenter Histology Image Integration and Multiscale Deep Learning for Machine Learning-Enabled Pediatric Sarcoma Classification

Pediatric sarcomas are rare and diverse, often leading to misclassification that hampers prognosis and treatment planning. We collected and harmonized...

CLIF-Net: Intersection-guided Cross-view Fusion Network for Infection Detection from Cranial Ultrasound

This paper addresses the problem of detecting possible serious bacterial infection (pSBI) of infancy, i.e. a clinical presentation consistent with bac...

Omics Integration Uncovers Mechanisms Associated with HIV Viral Load and Potential Therapeutic Insights

While antiretroviral therapy (ART) has significantly improved disease prognosis in people with HIV (PWH), understanding the biological mechanisms unde...

A conversational agent for providing personalized PrEP support – Protocol for chatbot implementation and evaluation

Chatbots have the potential to reduce barriers to pre-exposure prophylaxis (PrEP), including lack of awareness, misconceptions, and stigma, by providi...

Secure and Efficient Federated Learning for Predictive Modeling in Resource-Constrained Healthcare Systems

Predictive modeling in healthcare holds promise for improving clinical outcomes, but in many low-resource settings, data fragmentation, privacy concer...

MentalQLM: A lightweight large language model for mental healthcare based on instruction tuning and dual LoRA modules

Mental disorders pose significant challenges to healthcare systems and have profound social implications. The rapid development of large language mode...

Orchestrated multi agents sustain accuracy under clinical-scale workloads compared to a single agent

We tested state-of-the-art large language models (LLMs) in two configurations for clinical-scale workloads: a single agent handling heterogeneous task...

Predicting Tuberculosis Incidence in Adult HIV Patients on ART in Debre Markos, Ethiopia: A Machine Learning Approach

Tuberculosis (TB) is the commonest comorbidity among individuals with HIV/AIDS, especially in low- and middle-income nations such as Ethiopia. Early d...