Risk Management

Checklist for Artificial Intelligence in Medical Imaging (CLAIM): 2024 Update.

To address the rapid evolution of artificial intelligence in medical imaging, the authors present th...

scGrapHiC: deep learning-based graph deconvolution for Hi-C using single cell gene expression.

SUMMARY: Single-cell Hi-C (scHi-C) protocol helps identify cell-type-specific chromatin interactions...

A review on legal issues of medical robots.

This paper examines the legal challenges associated with medical robots, including their legal statu...

Deliberate Problem-solving with a Large Language Model as a Brainstorm Aid Using a Checklist for Prompt Generation.

Large language models (LLMs) use autoregression to generate text in response to queries. Crafting an...

Protocol: revolutionizing central nervous system tumour diagnosis in low- and middle-income countries: an innovative observational study on intraoperative smear and deep learning.

OBJECTIVE: The aim of this study is to assess the feasibility and implementation of a novel approach...

AI for Detection of Tuberculosis: Implications for Global Health.

Tuberculosis, which primarily affects developing countries, remains a significant global health conc...

Understanding Liability Risk from Using Health Care Artificial Intelligence Tools.

Current Applications of Artificial Intelligence for Pediatric Dentistry: A Systematic Review and Meta-Analysis.

To systematically evaluate artificial intelligence applications for diagnostic and treatment planni...

Neurosurgery, Explainable AI, and Legal Liability.

One of the challenges of AI technologies is its "black box" nature, or the lack of explainability an...

Artificial intelligence in forensic medicine and related sciences - selected issues.

AIM: The aim of the work is to provide an overview of the potential application of artificial intell...

Deep Learning-Based Cell Tracking in Deforming Organs and Moving Animals.

Cell tracking is an essential step in extracting cellular signals from moving cells, which is vital ...

Implementation of a robot-mediated upper limb rehabilitation protocol for a customized treatment after stroke: A retrospective analysis.

BACKGROUND: Many authors have emphasized the need for individualized treatments in rehabilitation, b...

Prospective Comparison of Standard and Deep Learning-reconstructed Turbo Spin-Echo MRI of the Shoulder.

Background Deep learning (DL)-based MRI reconstructions can reduce imaging times for turbo spin-echo...

Deep Learning for Predicting Gene Regulatory Networks: A Step-by-Step Protocol in R.

Deep learning has emerged as a powerful tool for solving complex problems, including reconstruction ...

Challenges involved in the application of artificial intelligence in gastroenterology: The race is on!

Gastroenterology is a particularly data-rich field, generating vast repositories of data that are a ...

Ethical implications of AI and robotics in healthcare: A review.

Integrating Artificial Intelligence (AI) and robotics in healthcare heralds a new era of medical inn...

Determination of the melanin and anthocyanin content in barley grains by digital image analysis using machine learning methods.

The pigment composition of plant seed coat affects important properties such as resistance to pathog...

Artificial Intelligence in Medicine: Issues When Determining Negligence.

The introduction of novel medical technology, such as artificial intelligence (AI), into traditional...

Real-Time Monitoring for Aseptic Drilling: Lessons Learned from the Atacama Rover Astrobiology Drilling Studies Contamination Control Strategy and Implementation and Application to the Icebreaker Mars Life Detection Mission.

In 2019, the Atacama Rover Astrobiology Drilling Studies (ARADS) project field-tested an autonomous ...

Advances, trends and challenges in the use of biochar as an improvement strategy in the anaerobic digestion of organic waste: a systematic analysis.

A recently strategy applied to anaerobic digestion (AD) is the use of biochar (BC) obtained from the...

Artificial intelligence and clinical decision support: clinicians' perspectives on trust, trustworthiness, and liability.

Artificial intelligence (AI) could revolutionise health care, potentially improving clinician decisi...