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Identifying and Reporting Dependent Adult abuse

Latest AI and machine learning research in identifying and reporting dependent adult abuse for healthcare professionals.

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Rethinking Byzantine Robustness in Federated Recommendation from Sparse Aggregation Perspective

To preserve user privacy in recommender systems, federated recommendation (FR) based on federated learning (FL) emerges, keeping the personal data on the local client and updating a model collaboratively. Unlike FL, FR has a unique sparse aggregation mechanism, where the embedding of each item is updated by only partial clients, instead of full clients in a dense aggregation of general FL. Recen...

COph100: A comprehensive fundus image registration dataset from infants constituting the "RIDIRP" database

Retinal image registration is vital for diagnostic therapeutic applications within the field of ophthalmology. Existing public datasets, focusing on adult retinal pathologies with high-quality images, have limited number of image pairs and neglect clinical challenges. To address this gap, we introduce COph100, a novel and challenging dataset known as the Comprehensive Ophthalmology Retinal Image...

Neural Timescale of Adolescents Major Depressive Disorder

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

Screening and machine-learning assisted prediction of translation-enhancing peptides reducing ribosomal stalling in Escherichia coli

We previously reported that the nascent SKIK peptide enhances translation and alleviates ribosomal stalling caused by arrest peptides (APs) such as Se...

Inferring the landscapes of mutation and recombination in the common marmoset (Callithrix jacchus) in the presence of twinning and hematopoietic chimerism

The common marmoset is an important model in biomedical and clinical research, particularly for the study of age-related, neurodegenerative, and neuro...

Accurate detection and quantification of single-base m6A RNA modification using nanopore signals with multi-view deep learning

N6-methyladenosine (m6A) is a crucial epitranscriptomic mark. While Nanopore Direct RNA Sequencing (DRS) enables transcriptome-wide detection, most ex...

MechanoAge, a machine learning platform to identify individuals susceptible to breast cancer based on mechanical properties of single cells

Existing breast cancer risk models inadequately identify individuals at latent risk, particularly among women without known genetic mutations or famil...

A structure-informed evolutionary model for predicting viral immune escape and evolution

Persistent emergence of viral variants capable of evading host immunity constitutes a significant threat to public health. This antigenic evolution fr...

Intelligent Tool Orchestration for Rapid Mechanistic Model Prototyping: MCP Servers as AI-Biology Interfaces

The construction of multicellular mechanistic models in systems biology typically requires months of literature research, programming expertise, and d...

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 unified model of short- and long-term plasticity: Effects on network connectivity and information capacity

Activity-dependent synaptic plasticity is a fundamental learning mechanism that shapes connectivity and activity of neural circuits. Existing computat...

Decoding Diabetes: Harnessing AI to Accurately Predict Real-Time and Future Blood Glucose Levels for Diabetes Management Using Diet, Exercise, Insulin Intake, and Heart Rate Variability

Continuous glucose monitoring (CGM) systems play a crucial role in diabetes care. Yet, they focus solely on blood glucose levels (BGL), neglect diet, ...

Refined shoulder kinematics via markerless bony landmark detection and acromial 3D shape using an RGB-D camera during hand-cycling

Biomechanical biofeedback has the potential to enhance rehabilitation by providing clinicians with objective evaluation of patient performances. As fe...

Pseudodynamics+: Reconstructing Population Dynamics from Time-Resolved Single Cell Landscapes with Physics Informed Neural Networks

Single-cell profiling provides snapshots of the heterogeneous states that characterise developmental processes, organ regeneration and progression tow...

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...

Systematic Exploration of Hospital Cost Variability: A Conformal Prediction-Based Outlier Detection Method for Electronic Health Records

Marked variability in inpatient hospitalization costs poses significant challenges to healthcare quality, resource allocation, and patient outcomes. T...

SPIRIT-CONSORT-TM: a corpus for assessing transparency of clinical trial protocol and results publications

Randomized controlled trials (RCTs) can produce valid estimates of the benefits and harms of therapeutic interventions. However, incomplete reporting ...

The Rise of the Large Language Models (LLMs): Can They Truly Match Clinical and Data Science Experts in Clinical Trial Data Analysis?

Clinical trials provide evidence of the efficacy and safety of experimental treatment regimens. Analysis of data from these trials is a time-intensive...

Detecting papilloedema as a marker of raised intracranial pressure using artificial intelligence: a systematic review

Automated detection of papilloedema using artificial intelligence (AI) and retinal images acquired through an ophthalmoscope for triage of patients wi...

Neuromodulation with Ultrasound: Hypotheses on the Directionality of Effects and Community Resource

Low-intensity Transcranial Ultrasound Stimulation is a promising non-invasive technique for brain stimulation and focal neuromodulation. Research with...

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