The balance between artificial and human intelligence in clinical practice
Abstract
INTRODUCTION: Artificial intelligence (AI) is becoming increasingly integrated into clinical care in hand surgery. Its applications extend across diagnosis, planning, intraoperative assistance, postoperative monitoring, rehabilitation, prosthetics and education.
APPLICATIONS: In diagnostic imaging, AI improves the detection of distal radius and scaphoid fractures, estimates osteoporosis from hand radiographs, identifies triangular fibrocartilage complex injuries on magnetic resonance imaging, segments bones and cartilage, and supports dynamic wrist analysis; ultrasound- and neurophysiological-based models aid carpal tunnel syndrome diagnosis. Prognostic models predict outcomes after carpal tunnel release and thumb carpometacarpal osteoarthritis with mixed performance. Pre- and intraoperative applications include large language model-based triage and coding, navigation and phase/gesture recognition from surgical video, autonomous microsurgical prototypes and telemanipulator platforms for supermicrosurgery. Artificial intelligence-enabled telemonitoring (e.g. remote photoplethysmography) and video-based mobility tracking support postoperative care and rehabilitation. Vision-guided and multimodal sensing enhance myoelectric prosthesis control.
RISKS: Risks include data privacy and security, algorithmic bias (data, transposition, normative, annotation) and opacity, overreliance with automation bias and skill erosion, and unresolved legal and ethical questions (liability,…
Read the paper
Related studies
- Active Learning during Federated Learning for Object Detection
- Fairness-aware federated learning
- Decentralized Federated Learning
- Building a Personally Identifiable Information Recognizer in a Privacy Preserved Manner Using Automated Annotation and Federated Learning
- Preservation of Patient Level Privacy: Federated Classification and Calibration Models
- Efficient explainable federated learning
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.