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Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Acute appendicitis is a typical surgical emergency worldwide and one of the common causes of surgical acute abdomen in the elderly. Accurately diagnosing and differentiating acute appendicitis can assist clinicians in formulating a scientifi
Externí odkaz:
https://doaj.org/article/feada03a1a9b4e08812fa6bffcb20436
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-26 (2024)
Abstract Concrete compressive strength (CS) is a crucial performance parameter in concrete structure design. Reliable strength prediction reduces costs and time in design and prevents material waste from extensive mixture trials. Machine learning tec
Externí odkaz:
https://doaj.org/article/867cd2da4e6f4f9ebc1578d511e7c220
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-18 (2024)
Abstract This study employs machine learning to detect the severity of major depressive disorder (MDD) through binary and multiclass classifications. We compared models that used only biomarkers of oxidative stress with those that incorporate sociode
Externí odkaz:
https://doaj.org/article/02955352e2a24512962bd577050209e9
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract For the detection of food adulteration, sensitive and reproducible analytical methods are required. Liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) is a highly sensitive method that can be used to obtain analytic
Externí odkaz:
https://doaj.org/article/bf337a99b64248e4bf15fc5ade0476f5
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract We developed an interpretable machine learning algorithm that prospectively predicts the risk of thrombocytopenia in older critically ill patients during their stay in the intensive care unit (ICU), ultimately aiding clinical decision-making
Externí odkaz:
https://doaj.org/article/72144795a6824a0a8b3f65ea2c03b98c
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract Despite recent advances in surgical techniques and perinatal management in obstetrics for reducing intraoperative bleeding, blood transfusion may occur during a cesarean section (CS). This study aims to identify machine learning models with
Externí odkaz:
https://doaj.org/article/f62d9421a06d4d41ac5ace860fa9ce02
Autor:
Meng-Tong Wang, You-Ran Cai, Vlon Jang, Hong-Jian Meng, Ling-Bo Sun, Li-Min Deng, Yu-Wen Liu, Wen-Jin Zou
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Corneal infection is a major public health concern worldwide and the most common cause of unilateral corneal blindness. Toxic effects of different microorganisms, such as bacteria and fungi, worsen keratitis leading to corneal perforation ev
Externí odkaz:
https://doaj.org/article/a963b842015d4bf38646cc60b69682ca
Autor:
Ahao Wu, Lianghua Luo, Qingwen Zeng, Changlei Wu, Xufeng Shu, Pang Huang, Zhonghao Wang, Tengcheng Hu, Zongfeng Feng, Yi Tu, Yanyan Zhu, Yi Cao, Zhengrong Li
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract The study aims to investigate the predictive capability of machine learning algorithms for omental metastasis in locally advanced gastric cancer (LAGC) and to compare the performance metrics of various machine learning predictive models. A r
Externí odkaz:
https://doaj.org/article/7ef8e4f065c7465389c8cd0de86b29e5
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Cerebral aneurysms are a silent yet prevalent condition that affects a significant global population. Their development can be attributed to various factors, presentations, and treatment approaches. The importance of selecting the appropriat
Externí odkaz:
https://doaj.org/article/f4c656c5fdbe413b89eedc8bd16e642f
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract Symptoms of Acute Respiratory infections (ARIs) among under-five children are a global health challenge. We aimed to train and evaluate ten machine learning (ML) classification approaches in predicting symptoms of ARIs reported by mothers am
Externí odkaz:
https://doaj.org/article/3d835273b6ee4bde92e1b1dc76b38272