Latest AI and machine learning research in hospital-based medicine for healthcare professionals.
INTRODUCTION: Medication reconciliation (MR) in the emergency department (ED) is essential to ensure medication safety, especially for patients admitted to the hospital. However, performing MR for all ED patients, including those discharged, can be inefficient. To optimize prioritization, an artificial intelligence (AI)-powered hospital admission prediction dashboard was introduced. AIM: The prima...
BACKGROUND: Delirium remains one of the most consequential complications among critically ill patients in ICUs, exerting profound effects on morbidity, mortality, and annual healthcare costs exceeding $81 billion. Communication barriers between sedated or mechanically ventilated patients, their families, and multidisciplinary teams frequently delay recognition and impair management of delirium. Th...
Oncogenic RAS mutations, which are common in human tumors and occur in about 30Â % of cancer cases, present significant challenges to effective cancer ...
BACKGROUND: Research indicates that over 12% of patients undergoing coronary artery bypass grafting and more than 14% of patients undergoing surgical ...
OBJECTIVE: To evaluate the diagnostic accuracy and workflow efficiency of BioticsAI-anatomyUNet-0.1-2022 software in identifying 18 standard fetal ana...
Operative management of spinal metastatic disease is largely for symptom palliation rather than curative and revolves around the expectation that post...
BACKGROUND: We aimed to determine whether unsupervised machine learning was able to discover latent and possibly clinically-relevant clusters, hidden ...
Multidisciplinary team (MDT) discussions have become a cornerstone of colorectal cancer (CRC) management, integrating the expertise of surgeons, oncol...
OBJECTIVE: This study aims to develop and validate interpretable machine learning (ML) models to dynamically predict mortality risk among intensive ca...
What are the implications of the growing use of artificial intelligence (AI) in recruitment and hiring for organizational inequalities? While advocate...
Colorectal cancer (CRC) is the third most commonly diagnosed malignancy worldwide. Prognosis is significantly worsened in patients with colorectal liv...
OBJECTIVE: This narrative review synthesizes machine learning (ML) applications across the stroke and post-stroke continuum from acute imaging and dia...
Care transitions remain high-risk periods, with up to 28% of patients experiencing adverse events (AEs) or readmissions within 30 days of discharge. T...
Follicular lymphoma (FL), traditionally considered an indolent yet incurable malignancy, is experiencing a substantial evolution in its therapeutic la...
INTRODUCTION: Since the post-antibiotic era, there has been significant difficulty in treating infectious diseases due to the increase in antimicrobia...
BACKGROUND: The rise of digital health data has expanded opportunities for data-driven innovation, yet privacy, legal and ethical barriers frame data ...
OBJECTIVES: This study aimed to integrate soft tissue calcifications and ossifications (STCO) detected on cone beam computed tomography (CBCT) into an...
BACKGROUND: Independent ambulation at hospital discharge is a critical determinant of discharge destination and caregiving burden in older adults with...
Despite the exponential growth of artificial intelligence (AI) solutions designed to assist radiologists in clinical practice, their actual impact on ...
BACKGROUND: Clinical documentation is essential for safe, high-quality care but has become increasingly complex, contributing to clinician burnout. La...