Risk Management

Artificial Intelligence and Liability in Medicine: Balancing Safety and Innovation.

Policy Points With increasing integration of artificial intelligence and machine learning in medicine, there are concerns that algorithm inaccuracy could lead to patient injury and medical liability. While prior work has focused on medical malpractice, the artificial intelligence ecosystem consists of multiple stakeholders beyond clinicians. Current liability frameworks are inadequate to encourage...

A Protocol for the Diagnosis of Autism Spectrum Disorder Structured in Machine Learning and Verbal Decision Analysis.

Autism Spectrum Disorder is a mental disorder that afflicts millions of people worldwide. It is estimated that one in 160 children has traces of autism, with five times the higher prevalence in boys. The protocols for detecting symptoms are diverse. However, the following are among the most used: the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5), of the American Psychi...

The T.R.U.E. Checklist for Identifying Impactful Artificial Intelligence-Based Findings in Nuclear Medicine: Is It True? Is It Reproducible? Is It Useful? Is It Explainable?

Deep learning diagnostic and risk-stratification pattern detection for COVID-19 in digital lung auscultations: clinical protocol for a case-control and prospective cohort study.

BACKGROUND: Lung auscultation is fundamental to the clinical diagnosis of respiratory disease. However, auscultation is a subjective practice and inte...

Protocol for a reproducible experimental survey on biomedical sentence similarity.

Measuring semantic similarity between sentences is a significant task in the fields of Natural Language Processing (NLP), Information Retrieval (IR), ...

Raising the Bar for Randomized Trials Involving Artificial Intelligence: The SPIRIT-Artificial Intelligence and CONSORT-Artificial Intelligence Guidelines.

Artificial intelligence (AI)-based applications have the potential to improve the quality and efficiency of patient care in dermatology. Unique challe...

Target2DeNovoDrug: a novel programmatic tool for -deep learning based drug design for any target of interest.

The on-going data-science and Artificial Intelligence (AI) revolution offer researchers a fresh set of tools to approach structure-based drug design p...

A novel artificial intelligence protocol to investigate potential leads for diabetes mellitus.

Dipeptidyl peptidase-4 (DPP4) is highly participated in regulating diabetes mellitus (DM), and inhibitors of DPP4 may act as potential DM drugs. There...

Automatic deep learning-based pleural effusion classification in lung ultrasound images for respiratory pathology diagnosis.

Lung ultrasound (LUS) imaging as a point-of-care diagnostic tool for lung pathologies has been proven superior to X-ray and comparable to CT, enabling...

Clinical presentation of COVID-19 - a model derived by a machine learning algorithm.

COVID-19 pandemic has flooded all triage stations, making it difficult to carefully select those most likely infected. Data on total patients tested, ...

Accurate surface ultraviolet radiation forecasting for clinical applications with deep neural network.

Exposure to appropriate doses of UV radiation provides enormously health and medical treatment benefits including psoriasis. Typical hospital-based ph...

Toward assessing clinical trial publications for reporting transparency.

OBJECTIVE: To annotate a corpus of randomized controlled trial (RCT) publications with the checklist items of CONSORT reporting guidelines and using t...

Improved protein structure refinement guided by deep learning based accuracy estimation.

We develop a deep learning framework (DeepAccNet) that estimates per-residue accuracy and residue-residue distance signed error in protein models and ...

Fear Recognition for Women Using a Reduced Set of Physiological Signals.

Emotion recognition is benefitting from the latest research into physiological monitoring and wireless communications, among other remarkable achievem...

An interdisciplinary team-training protocol for robotic gynecologic surgery improves operating time and costs: analysis of a 4-year experience in a university hospital setting.

Main aim of this study is to assess the effect of a structured, interdisciplinary, surgical, team-training protocol in robotic gynecologic surgery, wi...

Barriers and facilitators to the implementation of social robots for older adults and people with dementia: a scoping review protocol.

BACKGROUND: Psychosocial health issues such as depression and social isolation are an important cause of morbidity and premature mortality for older a...

Designing deep learning studies in cancer diagnostics.

The number of publications on deep learning for cancer diagnostics is rapidly increasing, and systems are frequently claimed to perform comparable wit...

Integrated functional neuronal network analysis of 3D silk-collagen scaffold-based mouse cortical culture.

Bioengineered 3D tunable neuronal constructs are a versatile platform for studying neuronal network functions, offering numerous advantages over exist...

Facilitating information extraction without annotated data using unsupervised and positive-unlabeled learning.

Information extraction (IE), the distillation of specific information from unstructured data, is a core task in natural language processing. For rare ...

The 3D reconstructed skin micronucleus assay using imaging flow cytometry and deep learning: A proof-of-principle investigation.

The reconstructed skin micronucleus (RSMN) assay was developed in 2006, as an in vitro alternative for genotoxicity evaluation of dermally applied che...