In the past decade diabetes management has been transformed by the addition of continuous glucose monitoring and insulin pump data. More recently, a wide variety of functions and physiologic variables, such as heart rate, hours of sleep, number of steps walked and movement, have been available through wristbands or watches. New data, hydration, geolocation, and barometric pressure, among others, will be incorporated in the future. All these parameters, when analyzed, can be helpful for patients and doctors' decision support. Similar new scenarios have appeared in most medical fields, in such a way that in recent years, there has been an increased interest in the development and application of the methods of artificial intelligence (AI) to decision support and knowledge acquisition. Multidisciplinary research teams integrated by computer engineers and doctors are more and more frequent, mirroring the need of cooperation in this new topic. AI, as a science, can be defined as the ability to make computers do things that would require intelligence if done by humans. Increasingly, diabetes-related journals have been incorporating publications focused on AI tools applied to diabetes. In summary, diabetes management scenarios have suffered a deep transformation that forces diabetologists to incorporate skills from new areas. This recently needed knowledge includes AI tools, which have become part of the diabetes health care. The aim of this article is to explain in an easy and plane way the most used AI methodologies to promote the implication of health care providers-doctors and nurses-in this field.
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http://dx.doi.org/10.1177/1932296817710475 | DOI Listing |
Int J Surg
January 2025
Department of Cardiovascular Surgery, Xijing Hospital, Xi'an, Shaanxi, China.
Background: The impact of aortic arch (AA) morphology on the management of the procedural details and the clinical outcomes of the transfemoral artery (TF)-transcatheter aortic valve replacement (TAVR) has not been evaluated. The goal of this study was to evaluate the AA morphology of patients who had TF-TAVR using an artificial intelligence algorithm and then to evaluate its predictive value for clinical outcomes.
Materials And Methods: A total of 1480 consecutive patients undergoing TF-TAVR using a new-generation transcatheter heart valve at 12 institutes were included in this retrospective study.
Int J Surg
January 2025
Department of Surgery, Virgen del Rocio University Hospital, Seville, Spain.
Pancreatic surgery is considered one of the most challenging interventions by many surgeons, mainly due to retroperitoneal location and proximity to key and delicate vascular structures. These factors make pancreatic resection a demanding procedure, with successful rates far from optimal and frequent postoperative complications. Surgical planning is essential to improve patient outcomes, and in this regard, many technological advances made in the last few years have proven to be extremely useful in medical fields.
View Article and Find Full Text PDFInt J Surg
January 2025
Carcinoma Department of Traditional Chinese Medicine, Dianjiang People's Hospital of Chongqing, Chongqing, PR China.
The widespread adoption of high-resolution computed tomography (CT) screening has led to increased detection of small pulmonary nodules, necessitating accurate localization techniques for surgical resection. This review examines the evolution, efficacy, and safety of various localization methods for small pulmonary nodules. Studies focusing on localization techniques for pulmonary nodules ≤30 mm in diameter were included, with emphasis on technical success rates and complication profiles.
View Article and Find Full Text PDFNano Lett
January 2025
Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou 215123, P. R. China.
Along with the rapid development of the digital economy and artificial intelligence, heat sinks available for immersion phase-change liquid cooling (IPCLC) of chips are facing huge challenges. Here, we design a high-performance IPCLC heat sink based on a copper microgroove/nanocone (MGNC) composite structure. Maximal heat fluxes () of the MGNC structure, microgroove structure, and flat copper reach 112.
View Article and Find Full Text PDF3D Print Med
January 2025
Department of Pediatric Cardiology, The Heart Institute, University of Colorado, Children's Hospital Colorado, 13123 E 16th Ave B100, 80045, Aurora, CO, USA.
Background: Despite advancements in imaging technologies, including CT scans and MRI, these modalities may still fail to capture intricate details of congenital heart defects accurately. Virtual 3D models have revolutionized the field of pediatric interventional cardiology by providing clinicians with tangible representations of complex anatomical structures. We examined the feasibility and accuracy of utilizing an automated, Artificial Intelligence (AI) driven, cloud-based platform for virtual 3D visualization of complex congenital heart disease obtained from 3D rotational angiography DICOM images.
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