Latest AI and machine learning research in information technology for healthcare professionals.
BACKGROUND: Clinical natural language processing (NLP) models are widely used to extract information from electronic health records (EHR) and support healthcare decision-making. However, most existing models are evaluated under the assumption of static data distributions and fixed task definitions, overlooking the dynamic and evolving nature of real clinical environments. Distributional changes ar...
On July 9, 2025, the Midwest Pediatric Device Consortium hosted its second showcase at the MidTown Collaboration Center in Cleveland, OH. This meeting convened clinicians, engineers, regulators, entrepreneurs, and policy stakeholders to discuss the challenges and opportunities in pediatric medical device development. The program included expert panel discussions addressing value demonstration in h...
The rapid evolution of machine learning techniques, combined with the growing availability of large and diverse data sets, is poised to transform hear...
Developing effective health care teams is critical to meet the rising complexity in patient care. However, optimizing team composition, interpersonal ...
BACKGROUND: Out-of-hospital cardiac arrest (OHCA) is a public health burden with the majority occurring in the general population for whom there is no...
This paper presents an AI-driven multisensor wearable system for real-time breathing pattern recognition by integrating an inertial measurement unit (...
Artificial intelligence (AI) is widely regarded as a key technology for the further development of medical care. Its performance, however, depends les...
OBJECTIVE: Assess whether a single instance-segmentation model can operate robustly across multiple cytological stains, avoiding stain-specific pipeli...
Automated phenotyping in ophthalmology requires accurate standardization of clinical terms to facilitate interoperability and research. This study eva...
Insider threats remain among the most critical challenges in cybersecurity, as malicious or compromised employees can bypass traditional defences and ...
Chagas disease affects 6-7 million people worldwide and causes approximately 12,000 deaths annually. Diagnostic methods vary by disease stage, with se...
Artificial Intelligence (AI) is rapidly transforming cancer care by enabling healthcare teams to make more accurate diagnoses, predict responses to th...
OBJECTIVES: To develop a large-language-model (LLM)-centric workflow flow extraction and migration of clinician-documented colonoscopy recall recommen...
Accurate, objective assessment of hip joint range of motion (ROM) is essential for orthopedic diagnosis and rehabilitation. Conventional tools, such a...
This paper introduces a novel IoT-Enhanced Virtual Power Plant (VPP) framework that integrates edge-fog computing, blockchain-secured communication, a...
The malicious URLs have been a constant threat to cybersecurity because hackers are constantly creating phishing, malware, spam, and defacement links ...
Neuroradiologists are constantly asked to adapt their practice and implement changes that align with the latest scientific evidence, such as new strok...
BACKGROUND: Cybersecurity attacks in healthcare have increased in number and severity over the last decade. Healthcare targets are ten times more valu...
The quick expansion of Internet of Things (IoT) devices has presented new cybersecurity challenges, with botnet attacks posing noteworthy threats to n...
BACKGROUND: Long COVID affects a substantial proportion of the over 778 million individuals infected with SARS-CoV-2, yet predictive models remain lim...