Although several left ventricular assist devices (LVADs) have been used widely, remote monitoring of LVAD parameters has been available only recently. We present our remote monitoring experience with an axial-flow LVAD (HeartAssist-5, MicroMed Cardiovascular, Inc., Houston, TX, USA). Five consecutive patients who were implanted a HeartAssist-5 LVAD because of end-stage heart failure due to ischemic (n=4) or idiopathic (n=1) cardiomyopathy, and discharged from hospital between December 2011 and January 2013 were analyzed. The data (pump speed, pump flow, power consumption) obtained from clinical visits and remote monitoring were studied. During a median follow-up of 253 (range: 80-394) days, fine tuning of LVADs was performed at clinical visits. All patients are doing well and are in New York Heart Association Class-I/II. A total of 39 alarms were received from three patients. One patient was hospitalized for suspected thrombosis and was subjected to physical examinations as well as laboratory and echocardiographic evaluations; however, no evidence of thrombus washout or pump thrombus was found. The patient was treated conservatively. Remaining alarms were due to insufficient water intake and were resolved by increased water consumption at night and summer times, and fine tuning of pump speed. No alarms were received from the remaining two patients. We believe that remote monitoring is a useful technology for early detection and treatment of serious problems occurring out of hospital thereby improving patient care. Future developments may ease troubleshooting, provide more data from the patient and the pump, and eventually increase physician and patient satisfaction. Despite all potential clinical benefits, remote monitoring should be taken as a supplement to rather than a substitute for routine clinical visits for patient follow-up.
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PLoS One
January 2025
North China Institute of Aerospace Engineering, Langfang, China.
As the global economy expands, waterway transportation has become increasingly crucial to the logistics sector. This growth presents both significant challenges and opportunities for enhancing the accuracy of ship detection and tracking through the application of artificial intelligence. This article introduces a multi-object tracking system designed for unmanned aerial vehicles (UAVs), utilizing the YOLOv7 and Deep SORT algorithms for detection and tracking, respectively.
View Article and Find Full Text PDFPLoS One
January 2025
Dirección General de Minería, República Dominicana.
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View Article and Find Full Text PDFAdv Skin Wound Care
January 2025
At the Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, United States, Adrian Chen, BS, Aleksandra Qilleri, BS, and Timothy Foster, BS, are Medical Students. Amit S. Rao, MD, is Project Manager, Department of Surgery, Wound Care Division, Northwell Wound Healing Center and Hyperbarics, Northwell Health, Hempstead. Sandeep Gopalakrishnan, PhD, MAPWCA, is Associate Professor and Director, Wound Healing and Tissue Repair Analytics Laboratory, School of Nursing, College of Health Professions, University of Wisconsin-Milwaukee. Jeffrey Niezgoda, MD, MAPWCA, is Founder and President Emeritus, AZH Wound Care and Hyperbaric Oxygen Therapy Center, Milwaukee, and President and Chief Medical Officer, WebCME, Greendale, Wisconsin. Alisha Oropallo, MD, is Professor of Surgery, Donald and Barbara Zucker School of Medicine and The Feinstein Institutes for Medical Research, Manhasset New York; Director, Comprehensive Wound Healing Center, Northwell Health; and Program Director, Wound and Burn Fellowship program, Northwell Health.
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View Article and Find Full Text PDFOphthalmol Ther
January 2025
International Health Policy Program (IHPP), Ministry of Public Health, Nonthaburi, Thailand.
Introduction: Screening diabetic retinopathy (DR) for timely management can reduce global blindness. Many existing DR screening programs worldwide are non-digital, standalone, and deployed with grading retinal photographs by trained personnel. To integrate the screening programs, with or without artificial intelligence (AI), into hospital information systems to improve their effectiveness, the non-digital workflow must be transformed into digital.
View Article and Find Full Text PDFEnviron Monit Assess
January 2025
Department of Landscape Architecture, Remote Sensing and GIS Laboratory, University of Cukurova, Adana, 01330, Turkey.
Recent advancements in satellite technology have greatly expanded data acquisition capabilities, making satellite imagery more accessible. Despite these strides, unlocking the full potential of satellite images necessitates efficient interpretation. Image classification, a widely adopted for extracting valuable information, has seen a surge in the application of deep learning methodologies due to their effectiveness.
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