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SchizoLMNet: a modified lightweight MobileNetV2- architecture for automated schizophrenia detection using EEG-derived spectrograms.
Phys Eng Sci Med
January 2025
Department of Electronics and Communication Engineering, Vishnu Institute of Technology, Bhimavaram, Andhra Pradesh, 534202, India.
Schizophrenia (SZ) is a chronic neuropsychiatric disorder characterized by disturbances in cognitive, perceptual, social, emotional, and behavioral functions. The conventional SZ diagnosis relies on subjective assessments of individuals by psychiatrists, which can result in bias, prolonged procedures, and potentially false diagnoses. This emphasizes the crucial need for early detection and treatment of SZ to provide timely support and minimize long-term impacts.
View Article and Find Full Text PDFRisk factors and resolution of patient-reported pain and mental health symptoms following rib fracture(s).
J Trauma Acute Care Surg
January 2025
From the Department of Surgery, University of Minnesota Medical School (M.S., K.S.); Department of Surgery (E.K.J., D.M., J.M.-D.), University of Minnesota; Fairview Health Services, Trauma Services, (M.B., M.D.); and Department of Surgery (G.B.M.-M., C.J.T.), Institute for Health Informatics (G.B.M.-M., C.T.), and Center for Learning Health System Sciences (G.B.M.-M., C.T.), University of Minnesota, Minneapolis, Minnesota.
Background: Rib fractures, constituting 10% to 15% of trauma admissions, contribute significantly to morbidity and mortality. Effective postdischarge patient care remains a challenge. Our system has operationalized patient-reported outcome measures (PROMs) via a mobile platform into routine postdischarge monitoring for rib fracture patients.
View Article and Find Full Text PDFEnhancing security and efficiency in Mobile Ad Hoc Networks using a hybrid deep learning model for flooding attack detection.
Sci Rep
January 2025
North Carolina School of Science and Mathematics, Durham, NC, 27705, USA.
Mobile Ad Hoc Networks (MANETs) are increasingly replacing conventional communication systems due to their decentralized and dynamic nature. However, their wireless architecture makes them highly vulnerable to flooding attacks, which can disrupt communication, deplete energy resources, and degrade network performance. This study presents a novel hybrid deep learning approach integrating Convolutional Neural Networks (CNN) with Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) architectures to effectively detect and mitigate flooding attacks in MANETs.
View Article and Find Full Text PDFMetaRehabVerse: The Great Opportunity to Put the Person's Functioning and Participation at the Center of Healthcare.
Neurorehabil Neural Repair
January 2025
Department of Mental and Physical Health and Preventive Medicine, University of Campania Luigi Vanvitelli, Naples, Italy.
Background And Objective: The metaverse refers to a digital realm accessible via internet connections using virtual reality and augmented reality glasses for promoting a new era of social rehabilitation. It represents the next-generation mobile computing platform expected to see widespread utilization in the future. In the context of rehabilitation, the metaverse is envisioned as a novel approach to enhance the treatment of human functioning exploiting the "synchronized brains" potential exacerbated by social interactions in virtual scenarios.
View Article and Find Full Text PDF3D Breast Scanning in Plastic Surgery Utilizing Free iPhone LiDAR Application: Evaluation, Potential, and Limitations.
Aesthet Surg J
January 2025
Department of Plastic and Reconstructive Surgery, Brussels University Hospital - Vrije Universiteit Brussel (VUB), Brussels, Belgium.
Article Synopsis
- Mobile LiDAR technology, using the iPhone's LiDAR scanner, offers an affordable alternative to traditional 3D imaging in plastic surgery, potentially increasing accessibility for surgical planning.
- In a study involving 25 patients, LiDAR measurements proved highly accurate for most breast measurements and showed excellent inter-rater reliability.
- The analysis indicated a significant cost reduction of 97.8% compared to conventional 3D systems, with measurement accuracy stabilizing after just a few uses.
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