Zobrazeno 1 - 10
of 554
pro vyhledávání: '"diabetes prediction"'
Publikováno v:
BMC Pregnancy and Childbirth, Vol 24, Iss 1, Pp 1-8 (2024)
Abstract Background Gestational Diabetes Mellitus (GDM) presents a significant health concern during pregnancy, predisposing individuals to future diabetes. Despite established postpartum diabetes screening guidelines, adherence to follow-up remains
Externí odkaz:
https://doaj.org/article/dd1b4f75d1ab4ecbbdcd0f60f7d81c7c
Autor:
Maryam Talebi Moghaddam, Yones Jahani, Zahra Arefzadeh, Azizallah Dehghan, Mohsen Khaleghi, Mehdi Sharafi, Ghasem Nikfar
Publikováno v:
BMC Medical Research Methodology, Vol 24, Iss 1, Pp 1-18 (2024)
Abstract Background Imbalanced datasets pose significant challenges in predictive modeling, leading to biased outcomes and reduced model reliability. This study addresses data imbalance in diabetes prediction using machine learning techniques. Utiliz
Externí odkaz:
https://doaj.org/article/4d2708e566e640e2a434ab6d39ae10b1
Autor:
Bianca de Almeida-Pititto, Julia Ines Branda, Julia M. de Oliveira, Patrícia M. Dualib, Luisa Bittencourt de Aquino Fernandes Dias, Isabela M. Bensenor, Paulo A. Lotufo, Sandra Roberta G. Ferreira
Publikováno v:
Endocrines, Vol 5, Iss 3, Pp 418-429 (2024)
Background: Type 2 diabetes mellitus (DM) is an important disease with an impact on public health globally. Early assessment is necessary with accessible markers, such as the TG/HDL ratio, in predicting DM. Methods: A total of 11,653 subjects from th
Externí odkaz:
https://doaj.org/article/203174fbb4b44c968f6916b0c3a732d1
Autor:
Jayakumar Kaliappan, I. J. Saravana Kumar, S. Sundaravelan, T. Anesh, R. R. Rithik, Yashbir Singh, Diana V. Vera-Garcia, Yassine Himeur, Wathiq Mansoor, Shadi Atalla, Kathiravan Srinivasan
Publikováno v:
Frontiers in Artificial Intelligence, Vol 7 (2024)
IntroductionIn the evolving landscape of healthcare and medicine, the merging of extensive medical datasets with the powerful capabilities of machine learning (ML) models presents a significant opportunity for transforming diagnostics, treatments, an
Externí odkaz:
https://doaj.org/article/cb09d0f2813f4d72baeb751787eda63b
Publikováno v:
IEEE Access, Vol 12, Pp 71535-71554 (2024)
The study investigates the intricate influence of gender and age variability in individuals diagnosed with diabetes, aiming to gain a comprehensive understanding of the diverse impact and implications of this prevalent metabolic disorder. A real-worl
Externí odkaz:
https://doaj.org/article/e224885ac9484ee7964aab1aff36c061
Publikováno v:
IEEE Access, Vol 12, Pp 66516-66538 (2024)
Diabetes is a metabolic disease caused by the body’s failure to use insulin or break down meals correctly. Every year, an alarming number of new cases of diabetes are recorded. A poor lifestyle and an unfavorable environment are the two main causes
Externí odkaz:
https://doaj.org/article/e416720f35f04aa5ba904d0f81a8cc3a
Autor:
Ritu Kapur, Yashwant Kumar, Ritik Sharma, Shivani Sharma, Eishkaran Singh, Dhruv Rohilla, Vikrant Kanwar, Bhupender Kumar, Arnav Bhavsar, Varun Dutt
Publikováno v:
IEEE Access, Vol 12, Pp 59346-59360 (2024)
Diabetes is a metabolic disorder often diagnosed late and requires continuous monitoring of blood glucose. We introduce GlucoBreath, a user-centric, cost-effective, and portable pre-diagnostic solution to address this global challenge. GlucoBreath ad
Externí odkaz:
https://doaj.org/article/68e26546a38743e29b7ef997dcaec0ec
Publikováno v:
Algorithms, Vol 17, Iss 11, p 519 (2024)
This study aimed to explore the potential of predicting diabetes by analyzing trends in plantar thermal and plantar pressure data, either individually or in combination, using various machine learning techniques. A total of twenty-six participants, c
Externí odkaz:
https://doaj.org/article/8cadb3c88ec643bf8c9f71eebffcaaa1
Publikováno v:
Biomedicines, Vol 12, Iss 8, p 1916 (2024)
Diabetes is a global epidemic with severe consequences for individuals and healthcare systems. While early and personalized prediction can significantly improve outcomes, traditional centralized prediction models suffer from privacy risks and limited
Externí odkaz:
https://doaj.org/article/389dd5533b314e05bbe962840b78b4c8
Publikováno v:
مجله انفورماتیک سلامت و زیست پزشکی, Vol 10, Iss 2, Pp 125-140 (2023)
Introduction: Diabetes is a chronic disease worldwide, with an increasing annual death rate. Many health professionals seek innovative ways to detect and treat it early. Rapid advances in machine learning have improved disease diagnosis. However, bec
Externí odkaz:
https://doaj.org/article/9e34c03cb90149f18ed2510c842c4802