Domestic Violence

Instance elimination strategy for non-convex multiple-instance learning using sparse positive bags.

In some multiple instance learning (MIL) applications, positive bags are sparse (i.e. containing onl...

Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence.

INTRODUCTION: The Transparent Reporting of a multivariable prediction model of Individual Prognosis ...

Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning.

Theophylline, a typical representative of active pharmaceutical ingredients, was selected to study t...

Fuzzy rank-based fusion of CNN models using Gompertz function for screening COVID-19 CT-scans.

COVID-19 has crippled the world's healthcare systems, setting back the economy and taking the lives ...

Impact of Artificial Intelligence Decision Support Using Deep Learning on Breast Cancer Screening Interpretation with Single-View Wide-Angle Digital Breast Tomosynthesis.

Background The high volume of data in digital breast tomosynthesis (DBT) and the lack of agreement o...

Leveraging high-throughput screening data, deep neural networks, and conditional generative adversarial networks to advance predictive toxicology.

There are currently 85,000 chemicals registered with the Environmental Protection Agency (EPA) under...

Artificial intelligence reporting guidelines: what the pediatric radiologist needs to know.

There has been an exponential rise in artificial intelligence (AI) research in imaging in recent yea...

Reporting of prognostic clinical prediction models based on machine learning methods in oncology needs to be improved.

OBJECTIVE: Evaluate the completeness of reporting of prognostic prediction models developed using ma...

Developing a reporting guideline for artificial intelligence-centred diagnostic test accuracy studies: the STARD-AI protocol.

INTRODUCTION: Standards for Reporting of Diagnostic Accuracy Study (STARD) was developed to improve ...

A multi-conformational virtual screening approach based on machine learning targeting PI3Kγ.

Nowadays, more and more attention has been attracted to develop selective PI3Kγ inhibitors, but the ...

BARD: A Structured Technique for Group Elicitation of Bayesian Networks to Support Analytic Reasoning.

In many complex, real-world situations, problem solving and decision making require effective reason...

The successful implementation of the Navio robotic technology required 29 cases.

Robotic-assisted total knee arthroplasty (RA-TKA) has potential benefits of improved restoration of ...

Objective pain stimulation intensity and pain sensation assessment using machine learning classification and regression based on electrodermal activity.

An objective measure of pain remains an unmet need of people with chronic pain, estimated to be 1/3 ...

ECG for Screening Cardiac Abnormalities: The Premise and Promise of Machine Learning.

The future of basic science in orthopaedics and traumatology: Cassandra or Prometheus?

Orthopaedic and trauma research is a gateway to better health and mobility, reflecting the ever-incr...

Wide range of applications for machine-learning prediction models in orthopedic surgical outcome: a systematic review.

Background and purpose - Advancements in software and hardware have enabled the rise of clinical pre...

The emerging role of artificial intelligence in the reporting of prostate pathology.

Musculoskeletal trauma and artificial intelligence: current trends and projections.

Musculoskeletal trauma accounts for a significant fraction of emergency department visits and patien...

Computational representations of protein-ligand interfaces for structure-based virtual screening.

: Structure-based virtual screening (SBVS) is an essential strategy for hit identification. SBVS pri...

FTIR spectroscopy with machine learning: A new approach to animal DNA polymorphism screening.

Technological advances in recent decades, especially in molecular genetics, have enabled the detecti...

Machine Learning Boosted Docking (HASTEN): An Open-source Tool To Accelerate Structure-based Virtual Screening Campaigns.

The software macHine leArning booSTEd dockiNg (HASTEN) was developed to accelerate structure-based v...