Latest AI and machine learning research in information technology for healthcare professionals.
BACKGROUND: Processing scanned documents in electronic health records (EHR) was one of the problem i...
OBJECTIVE: This study uses probabilistic independence to disentangle patient-specific sources of dis...
When a deep learning model is trained sequentially on different datasets, it often forgets the knowl...
Although still limited, the integration of artificial intelligence (AI) in health care has rapidly e...
OBJECTIVE: Electronic health records (EHR) are widely available to complement administrative data-ba...
OBJECTIVES: As large language models (LLMs) are integrated into electronic health record (EHR) workf...
BackgroundLet's Talk Tech (LTT) is a self-administered web intervention for people with memory loss ...
Cancer screening, leading to early detection, saves lives. Unfortunately, existing screening techn...
Large Language Models (LLMs) are being extensively used for cybersecurity purposes. One of them is...
Malware detection and classification remains a topic of concern for cybersecurity, since it is bec...
We present EHRMIND, a practical recipe for adapting large language models (LLMs) to complex clinic...
The digitization of cultural heritage collections has opened new directions for research, yet the ...
The emergence of scaling laws has profoundly shaped the development of large language models (LLMs...
Retinal imaging has emerged as a powerful, non-invasive modality for detecting and quantifying bio...
Electronic Health Records (EHR) offer rich real-world data for personalized medicine, providing in...
The rise of electronic health records (EHRs) has unlocked new opportunities for medical research, ...
Ransomware remains a critical threat to cybersecurity, yet publicly available datasets for trainin...
Conventional machine learning models, particularly tree-based approaches, have demonstrated promis...
Digital health technologies, including artificial intelligence, offer immense potential to revolutio...
Unsupervised anomaly detection (UAD) in medical imaging is crucial for identifying pathological ab...
Foundation models hold significant promise in healthcare, given their capacity to extract meaningf...