Latest AI and machine learning research in information technology for healthcare professionals.
Rare diseases affect an estimated 300-400 million people worldwide, yet individual conditions ofte...
Large-scale pretraining has transformed modeling of language and other data types, but its potenti...
OBJECTIVE: A large proportion of electronic health record (EHR) data consists of unstructured medica...
Starting in the 1970s with robots that were physically isolated from contact with their human co-wor...
We present Federated Timeline Synthesis (FTS), a novel framework for training generative foundatio...
Identification of key variables such as medications, diseases, relations from health records and c...
With current advancement in hybermedia knowledges, the privacy of digital information has develope...
Quantum Neural Networks (QNNs), a prominent approach in Quantum Machine Learning (QML), are emergi...
Magnetic Resonance Fingerprinting (MRF) is a fast quantitative MR Imaging technique that provides ...
Patient cohort retrieval is a pivotal task in medical research and clinical practice, enabling the...
Multivariate time series anomaly detection (MTS-AD) is critical in domains like healthcare, cybers...
Retrieval-Augmented Generation (RAG) systems are emerging as a key approach for grounding Large La...
The emergence of new-generation artificial intelligence technology has brought numerous innovations ...
Electronic Health Records (EHR)-based disease prediction models have demonstrated significant clin...
The integration of AI/ML into medical devices is rapidly transforming healthcare by enhancing diag...
Chest X ray (CXR) imaging remains a critical diagnostic tool for thoracic conditions, but current ...
Electronic Health Record (EHR) data encompass diverse modalities -- text, images, and medical code...
The Medical Information Mart for Intensive Care (MIMIC) datasets have become the Kernel of Digital...
The concept bottleneck model (CBM), as a technique improving interpretability via linking predicti...
We explore the role of ontologies in enhancing hybrid modeling and simulation through improved sem...
Accurate classification of software bugs is essential for improving software quality. This paper p...