AIMC Topic: Artificial Intelligence

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Understanding metric-related pitfalls in image analysis validation.

Nature methods
Validation metrics are key for tracking scientific progress and bridging the current chasm between artificial intelligence research and its translation into practice. However, increasing evidence shows that, particularly in image analysis, metrics ar...

Monitoring Mental Health: Legal and Ethical Considerations of Using Artificial Intelligence in Psychiatric Wards.

American journal of law & medicine
Artificial intelligence (AI) is being tested and deployed in major hospitals to monitor patients, leading to improved health outcomes, lower costs, and time savings. This uptake is in its infancy, with new applications being considered. In this Artic...

An Artificial Intelligence Chatbot is an Accurate and Useful Online Patient Resource Prior to Total Knee Arthroplasty.

The Journal of arthroplasty
BACKGROUND: Online information is a useful resource for patients seeking advice on their orthopaedic care. While traditional websites provide responses to specific frequently asked questions (FAQs), sophisticated artificial intelligence tools may be ...

A foundation for evaluating the surgical artificial intelligence literature.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
With increasing growth in applications of artificial intelligence (AI) in surgery, it has become essential for surgeons to gain a foundation of knowledge to critically appraise the scientific literature, commercial claims regarding products, and regu...

Artificial intelligence technology improves the accuracy of preoperative planning in primary total hip arthroplasty.

Asian journal of surgery
OBJECTIVE: Successful total hip arthroplasty relies on accurate preoperative planning. However, the conventional preoperative planning, a two-dimensional method using X-ray template, has shown poor reliability of predicting component size. To our kno...

Prediction of spontaneous distal ureteral stone passage using artificial intelligence.

International urology and nephrology
PURPOSE: Identifying factors predicting the spontaneous passage of distal ureteral stones and evaluating the effectiveness of artificial intelligence in prediction.

NAIF: A novel artificial intelligence-based tool for accurate diagnosis of stage F3/F4 liver fibrosis in the general adult population, validated with three external datasets.

International journal of medical informatics
OBJECTIVE: The purpose of this study was to determine the effectiveness of a new AI-based tool called NAIF (NAFLD-AI-Fibrosis) in identifying individuals from the general population with advanced liver fibrosis (stage F3/F4). We compared NAIF's perfo...