|
|
|
|
|
Rejath Jose, Faiz Syed, Anvin Thomas and Milan Toma
The advancement of machine learning in healthcare offers significant potential for enhancing disease prediction and management. This study harnesses the PyCaret library?a Python-based machine learning toolkit?to construct and refine predictive models for...
ver más
|
|
|
|
|
|
|
|
|
|
|
Shadi AlZu?bi, Mohammad Elbes, Ala Mughaid, Noor Bdair, Laith Abualigah, Agostino Forestiero and Raed Abu Zitar
Diabetes is a metabolic disorder in which the body is unable to properly regulate blood sugar levels. It can occur when the body does not produce enough insulin or when cells become resistant to insulin?s effects. There are two main types of diabetes, Ty...
ver más
|
|
|
|
|
|
|
|
|
|
|
Thomas T. H. Wan and Hunter S. Wan
Context. This commentary is based on an innovative approach to the development of predictive analytics. It is centered on the development of predictive models for varying stages of chronic disease through integrating all types of datasets, adds various n...
ver más
|
|
|
|
|
|
|
|
|
|
|
Lisa Ariellah Ward, Gulzar H. Shah, Jeffery A. Jones, Linda Kimsey and Hani Samawi
This paper examines the efficacy of telemedicine (TM) technology compared to traditional face-to-face (F2F) visits as an alternative healthcare delivery service for managing diabetes in populations residing in urban medically underserved areas (UMUPAs). ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Md. Ashikur Rahman, Lway Faisal Abdulrazak, Md. Mamun Ali, Imran Mahmud, Kawsar Ahmed and Francis M. Bui
Diabetes is one of the fatal diseases that play a vital role in the growth of other diseases in the human body. From a clinical perspective, the most significant approach to mitigating the effects of diabetes is early-stage control and management, with t...
ver más
|
|
|
|
|
|
|
|
|
|
|
Rafiya Sohail, Yousaf Saeed, Abid Ali, Reem Alkanhel, Harun Jamil, Ammar Muthanna and Habib Akbar
Diabetes is a chronic disease that is escalating day by day and requires 24/7 continuous management. It may cause many complications, precisely when a patient moves, which may risk their and other drivers? and pedestrians? lives. Recent research shows di...
ver más
|
|
|
|
|
|
|
|
|
|
|
Se Yun Jeong, Kwang Ho Lee, Jae Kwan Kim, Dohee Ahn, Hyemin Kim, Sang J. Chung, Sun-Young Yoon and Ki Hyun Kim
Ginkgo biloba L. (Ginkgoacea) contains an abundance of beneficial compounds and has demonstrated positive clinical effects in the management of metabolic syndrome. Recent studies have emphasized its efficacy against type 2 diabetes mellitus (T2DM), inclu...
ver más
|
|
|
|
|
|
|
|
|
|
|
Anna Sigridur Islind,Helena Vallo Hult
New self-care practices, such as self-management of chronic diseases, have emerged through mobile applications and devices, often designed, developed, and used outside the healthcare context. The development may lead to increased patient empowerment, sha...
ver más
|
|
|
|
|
|
|
|
|
|
|
Prawej Ansari, Samia Akther, Joyeeta T. Khan, Sara S. Islam, Md. Samim R. Masud, Anisur Rahman, Veronique Seidel and Yasser H. A. Abdel-Wahab
Diabetes mellitus, a major cause of mortality around the globe, can result in several secondary complications, including diabetic foot syndrome, which is brought on by diabetic neuropathy and ischemia. Approximately 15% of diabetic patients suffer from d...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mudassir M. Rashid, Mohammad Reza Askari, Canyu Chen, Yueqing Liang, Kai Shu and Ali Cinar
Artificial intelligence (AI) algorithms can provide actionable insights for clinical decision-making and managing chronic diseases. The treatment and management of complex chronic diseases, such as diabetes, stands to benefit from novel AI algorithms ana...
ver más
|
|
|
|
|
|