Clinical Trial Assessment Principles for High-Risk Medical Devices in the European Union: How Long Short-Term Memory (LSTM) Neural Networks Integrate
Year: 2025
Type: article
Abstract: High-risk medical devices within the European Union (EU) require strict frameworks for both assessments and surgical device regulations which focus on device safety alongside effectiveness and extended monitoring of the marketplace. This article describes the main processes that determine high-risk medical device testing within EU regulatory requirements. The research describes the application of sophisticated machine learning methods including LSTM neural networks to process refined and time-oriented clinical information. The specialized patternfinding capability of LSTMs allows them to examine temporal data sequences which generates forecasting capabilities to assist with risk assessment and evidence development. The investigation links regulatory science with AI to introduce an advanced method for boosting clinical trial assessment processes which results in accelerated and dependable choices during medical device approval.
Authors: Biomedical Scientist, MBA, Gerasimos Bobis, Chrysoula I Liakou, Dimitra Tzamaria, MSc. Biology Science, Markos Plytas, Marios Papadakis
Language: English
Topic: Healthcare Regulation
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4409979201