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Domestic Violence

Latest AI and machine learning research in domestic violence for healthcare professionals.

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Large language models streamline automated systematic review: A preliminary study

Large Language Models (LLMs) have shown promise in natural language processing tasks, with the potential to automate systematic reviews. This study evaluates the performance of three state-of-the-art LLMs in conducting systematic review tasks. We assessed GPT-4, Claude-3, and Mistral 8x7B across four systematic review tasks: study design formulation, search strategy development, literature scree...

CROPS: Model-Agnostic Training-Free Framework for Safe Image Synthesis with Latent Diffusion Models

With advances in diffusion models, image generation has shown significant performance improvements. This raises concerns about the potential abuse of image generation, such as the creation of explicit or violent images, commonly referred to as Not Safe For Work (NSFW) content. To address this, the Stable Diffusion model includes several safety checkers to censor initial text prompts and final ou...

Neural Timescale of Adolescents Major Depressive Disorder

Adolescent major depressive disorder (MDD) is characterized by heterogeneous symptomatology and complex neurodevelopmental underpinnings. Here, we inv...

Microdroplet screening rapidly profiles a biocatalyst to enable its AI-assisted engineering

Engineering enzymes for increased efficiency is key to enabling sustainable, ‘green’ biocatalytic production processes in the chemical and pharmaceuti...

DeepRES: Deep learning enables reaction-based comprehensive enzyme screening

Enzymes accelerate biochemical reactions in living organisms, thus playing an important role in metabolism. Although metabolic pathway databases are g...

A Machine Learning Approach to Predicting Dyspnea with Noninvasive Biomarkers

Dyspnea is the subjective sensation of breathing discomfort. This symptom is highly prevalent in patients with chronic and critical illness, and its p...

Extracellular Vesicle Gene Expression Enables Sensitive Detection of Colorectal Neoplasia

Extracellular vesicles (EVs), including exosomes, are emerging as promising carriers of disease-specific biomarkers due to their molecular cargo refle...

Accelerating Drug Discovery with HyperLab: An Easy-to-Use AI-Driven Platform

HyperLab, developed by HITS, is a web-based, AI-driven drug discovery platform designed to increase research efficiency for experimental drug discover...

Adaptive Feature-Weighted Stacking Ensemble for Short-Term Risk Prediction of Prolonged Length of Stay in Elderly Trauma Patients

The Adaptive Feature-Weighted Stacking Ensemble (AFWSE) model is presented here as a new machine learning method that provides staged prediction of pr...

Contrastive learning of adverse events to provide effective and interpretable vector representations for machine-assisted pharmacovigilance

Post-marketing surveillance is crucial for drug safety, yet the tools of pharmacovigilance rely solely on text-based data that may limit the applicabi...

Mechanical stretch disrupts calcium dynamics and redistributes Piezo1 in human astrocytes

Astrocytes regulate the activity of nearby neurons so disruption of astrocyte calcium dynamics by traumatic brain injury (TBI) could have profound con...

SLOGEN: A Structure-based Lead Optimization Model Unifying Fragment Generation and Screening

Lead optimization plays an important role in preclinical drug discovery. While deep learning has accelerated this process, structure-based approaches ...

Systematic Review of Artificial Intelligence use in behavioral analysis of invertebrate and larval model organisms: Methods, Applications and Future Recommendations

Invertebrate and larval model organisms such as Drosophila melanogaster, Caenorhabditis elegans, Danio rerio larvae, and Galleria mellonella are incre...

A PLM-Based Method for Predicting Protein Ion Channel Modulators for Drug Discovery and Safety Evaluation

Ion channels are central to regulating neuronal communication, cardiac rhythm, and muscle contraction. Their modulation can induce therapeutic benefit...

Ultrahigh throughput screening to train generative protein models for engineering specificity into unspecific peroxygenases

Enzyme engineering is central to developing biocatalysts with improved activity and specificity, yet traditional approaches are often limited by the s...

HyperBind2: Multi-Shot Learning Enables Progressive Improvement in Computational Antibody Discovery

Antibody discovery remains constrained by resource-intensive experimental screening approaches that offer limited control over critical properties. He...

Phenotypic Screening Coupled with AI-Driven Target Deconvolution Identifies α-Terthienyl as a Dual DPP-IV/HSD17β13 Modulator with Efficacy in a Mouse Model of MASLD

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a highly prevalent condition characterized by fat build-up in the liver and ranges...

Integration of artificial intelligence and high-content screening enabled identification of drugs for long-term treatment of cerebral cavernous malformation disease

Adults and children with cerebral cavernous malformations (CCMs) are at risk of experiencing lifelong complications such as hemorrhagic strokes, neuro...

Modeling trajectories of routine blood tests as dynamic biomarkers for outcome in spinal cord injury

Early outcome prediction after acute traumatic spinal cord injury (SCI) is challenging due to pathological complexities and population heterogeneity. ...

Electronic Health Record-Based Prediction Models to Inform Decisions about HIV Pre-exposure Prophylaxis: A Systematic Review

Several clinical prediction models have been developed using electronic health records data to help inform decisions about HIV pre-exposure prophylaxi...

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