AIMC Topic: Humans

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A novel missing data imputation approach based on clinical conditional Generative Adversarial Networks applied to EHR datasets.

Computers in biology and medicine
The missing data mechanism is a relevant problem in Machine Learning (ML) and biomedical informatics communities. Real-world Electronic Health Record (EHR) datasets comprise several missing values, thus revealing a high level of spatiotemporal sparsi...

Predicting Surgical Experience After Robotic Nerve-sparing Radical Prostatectomy Simulation Using a Machine Learning-based Multimodal Analysis of Objective Performance Metrics.

Urology practice
INTRODUCTION: Machine learning methods have emerged as objective tools to evaluate operative performance in urological procedures. Our objectives were to establish machine learning-based methods for predicting surgeon caseload for nerve-sparing robot...

Ethical considerations on artificial intelligence in dentistry: A framework and checklist.

Journal of dentistry
OBJECTIVE: Artificial Intelligence (AI) refers to the ability of machines to perform cognitive and intellectual human tasks. In dentistry, AI offers the potential to enhance diagnostic accuracy, improve patient outcomes and streamline workflows. The ...

Taxonomy of hybrid architectures involving rule-based reasoning and machine learning in clinical decision systems: A scoping review.

Journal of biomedical informatics
BACKGROUND: As the application of Artificial Intelligence (AI) technologies increases in the healthcare sector, the industry faces a need to combine medical knowledge, often expressed as clinical rules, with advances in machine learning (ML), which o...

Fetal magnetic resonance imaging artifacts: role of deep learning to improve imaging.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology

Supervised Text Classification System Detects Fontan Patients in Electronic Records With Higher Accuracy Than Codes.

Journal of the American Heart Association
Background The Fontan operation is associated with significant morbidity and premature mortality. Fontan cases cannot always be identified by () codes, making it challenging to create large Fontan patient cohorts. We sought to develop natural langua...

A systematic review on machine learning approaches in the diagnosis and prognosis of rare genetic diseases.

Journal of biomedical informatics
BACKGROUND: The diagnosis of rare genetic diseases is often challenging due to the complexity of the genetic underpinnings of these conditions and the limited availability of diagnostic tools. Machine learning (ML) algorithms have the potential to im...

Design, development and usability of an educational AI chatbot for People with Haemophilia in Senegal.

Haemophilia : the official journal of the World Federation of Hemophilia
INTRODUCTION: Gaps in the disease knowledge of People with Haemophilia (PWH) in Senegal are important barriers to the effective management of haemophilia. Digital health systems for chronic diseases in low- and middle-income countries are suggested t...

How AI can distort human beliefs.

Science (New York, N.Y.)
Models can convey biases and false information to users.

Optimal Combination of Mother Wavelet and AI Model for Precise Classification of Pediatric Electroretinogram Signals.

Sensors (Basel, Switzerland)
The continuous advancements in healthcare technology have empowered the discovery, diagnosis, and prediction of diseases, revolutionizing the field. Artificial intelligence (AI) is expected to play a pivotal role in achieving the goals of precision m...