OBJECTIVES: Integrating machine learning with Raman spectroscopy (RS) shows strong potential for intraoperative guidance in orthopedic procedures, but limited algorithm transparency remains a barrier to clinician trust. This study aims to develop int...
OBJECTIVE: Salivary hormone assessment is commonly used in menstrual cycle studies, but its validity for accurate menstrual cycle staging has been questioned. In the present study, we explore possibilities and limitations of salivary hormone assessme...
Computer methods and programs in biomedicine
Aug 1, 2025
BACKGROUND AND OBJECTIVE: The rapid growth of clinical data creates challenges in analysis and interpretation for medical professionals. To address these issues, we developed the Advanced Data Exploration and Processing Tool (ADEPT), integrating data...
Adverse events such as compulsory measures, absconding, illicit substance use, self-harm, aggressive behavior, and prolonged hospitalization pose significant challenges in forensic psychiatric inpatient care. This study introduces a machine learning-...
Accurate prediction of depressive symptoms in healthy individuals can enable early intervention and reduce both individual and societal costs. This study aimed to develop predictive models for depression in young adults using machine learning (ML) te...
Recently, artificial intelligence (AI) has emerged as a transformative tool, enhancing the speed, accuracy, and scalability of bacterial diagnostics. This review explores the role of AI in revolutionizing bacterial detection and antimicrobial suscept...
Accurate identification of clinically malignant pleural effusions is critical for cancer diagnosis and subsequent treatment planning. Here, surface-enhanced Raman spectroscopy (SERS) data of pleural effusions and serum carcinoembryonic antigen (CEA) ...
Journal of the experimental analysis of behavior
Jul 1, 2025
Traditionally, the experimental analysis of behavior has relied on the single discrete response paradigm (e.g., key pecks, lever presses, screen clicks) to identify behavioral patterns. However, the development and availability of new technology allo...
B-line artifacts in lung ultrasound, pivotal for diagnosing pulmonary conditions, warrant automated recognition to enhance diagnostic accuracy. In this paper, a lung ultrasound B-line vertical artifact identification method based on radio frequency (...
Central Apnea (CA) and Central Hypopnea (CH) are sleep disorders arising from the brain's inability to signal respiratory muscles, potentially leading to severe complications such as heart failure. This study presents a novel system for automating CA...
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