HIV/AIDS

Assessing Healthcare Stakeholder Understanding of Machine Learning Documentation.

Artificial Intelligence (AI) has significantly advanced clinical decision support systems in healthcare, particularly using Machine Learning (ML) models. However, the technical nature of current ML model documentation often leads to lack of comprehension among healthcare stakeholders. This study assessed the understanding of ML model documentation for a sepsis prediction model during an interdisci...

Analog Foundation Models

Analog in-memory computing (AIMC) is a promising compute paradigm to improve speed and power efficiency of neural network inference beyond the limits of conventional von Neumann-based architectures. However, AIMC introduces fundamental challenges such as noisy computations and strict constraints on input and output quantization. Because of these constraints and imprecisions, off-the-shelf LLMs a...

Flash-VL 2B: Optimizing Vision-Language Model Performance for Ultra-Low Latency and High Throughput

In this paper, we introduce Flash-VL 2B, a novel approach to optimizing Vision-Language Models (VLMs) for real-time applications, targeting ultra-lo...

"What Did You Say, ChatGPT?" The Use of AI in Black Women's HIV Self-Education: An Inductive Qualitative Data Analysis.

The emergence of widely accessible artificial intelligence (AI) chatbots such as ChatGPT presents unique opportunities and challenges in public health...

Emergence of accurate atomic energies from machine-learned noble-gas potentials.

The quantum theory of atoms in molecules gives access to well-defined local atomic energies. Due to their locality, these energies are potentially int...

Optimizing Neuro-Fuzzy and Colonial Competition Algorithms for Skin Cancer Diagnosis in Dermatoscopic Images

The rising incidence of skin cancer, coupled with limited public awareness and a shortfall in clinical expertise, underscores an urgent need for adv...

Thermal Detection of People with Mobility Restrictions for Barrier Reduction at Traffic Lights Controlled Intersections

Rapid advances in deep learning for computer vision have driven the adoption of RGB camera-based adaptive traffic light systems to improve traffic s...

Machine Learning-Driven Consensus Modeling for Activity Ranking and Chemical Landscape Analysis of HIV-1 Inhibitors.

This study aimed to develop a predictive model to classify and rank highly active compounds that inhibit HIV-1 integrase (IN). : A total of 2271 pote...

KNDM: A Knowledge Graph Transformer and Node Category Sensitive Contrastive Learning Model for Drug and Microbe Association Prediction.

It has been proven that the microbiome in human bodies can promote or inhibit the treatment effects of the drugs by affecting their toxicities and act...

Integrating different approaches for the identification of new disruptors of HIV-1 capsid multimerization.

Human Immunodeficiency Virus (HIV) belongs to the Lentivirus genus, Retroviridae family, enveloped by a lipid bilayer within which the capsid protein ...

Stigma Attitudes Toward HIV/AIDS From 2011 Through 2023 in Japan: Retrospective Study in Japan.

BACKGROUND: Stigma associated with HIV/AIDS continues to be a major barrier to prevention, management, and care. HIV stigma can negatively influence h...

IFPTML Multi-Output Model for Anti-Retroviral Compounds Including the Drug Structure and Target Protein Sequence Information.

Retroviruses such as HIV cause significant diseases in humans and other organisms, making the discovery of antiretroviral (ARV) drugs a critical prior...

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...

Promptable segmentation of CT lung lesions based on improved U-Net and Segment Anything model (SAM).

BackgroundComputed tomography (CT) is widely used in clinical diagnosis of lung diseases. The automatic segmentation of lesions in CT images aids in t...

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning

This paper proposes batch augmentation with unimodal fine-tuning to detect the fetus's organs from ultrasound images and associated clinical textual...

Qualitative Results from a Pilot Study of an Automated Directly Observed Therapy Intervention Using Artificial Intelligence with Conditional Economic Incentives among Young Adults with HIV.

Digitally monitoring and supporting daily antiretroviral therapy (ART) is a promising strategy for enhanced adherence among young adults with HIV (YWH...

Piezoelectric nanofiber-based intelligent hearing system.

Hearing loss, affecting individuals of all ages, can impair education, social function, and quality of life. Current treatments, such as hearing aids ...

Identification of genetic indicators linked to immunological infiltration in idiopathic pulmonary fibrosis.

This study employed bioinformatics to investigate potential molecular markers associated with idiopathic pulmonary fibrosis (IPF) and examined their c...

Exploring the potential biomarkers and potential causality of Ménière disease based on bioinformatics and machine learning.

Meniere disease (MD) is a common inner ear disorder closely related to immune abnormalities, but research on the characteristic genes between MD and i...

Exploring machine learning approaches for efficient image forgery detection.

In the digital age, accessible image manipulation raises concerns about authenticity, with forgery techniques threatening personal, journalistic, and ...