Yoga practices effect on VCSS-based classification of patients with chronic venous insufficiency based on hybrid machine learning algorithms by Changhong Pan, Lu Qi, Lili Zhao, Yijun Wei

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Novel genes involved in vascular dysfunction of the middle temporal gyrus in Alzheimer’s disease: transcriptomics combined with machine learning analysis by Meiling Wang, Aojie He, Yubing Kang, Zhaojun Wang, Yahui He, Kahleong Lim, Chengwu Zhang, Li Lu

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Machine learning identifies the association between second primary malignancies and postoperative radiotherapy in young-onset breast cancer patients. by Yulin Lai, Peiyuan Huang

“…<h4>Methods</h4>Machine learning components, including ridge regression, XGBoost, k-nearest neighbor, light gradient boosting machine, logistic regression, support vector machine, neural network, and random forest, were used to construct a predictive model and identify the risk factors for SPMs with data from the Surveillance, Epidemiology and End Results. …”
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The role of CTGF and MFG-E8 in the prognosis assessment of SCAP: a study combining machine learning and nomogram analysis by Tingting Lin, Tingting Lin, Huimin Wan, Jie Ming, Yifei Liang, Linxin Ran, Jingjing Lu

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Classifying Food Items During an Eating Occasion: A Machine Learning Approach with Slope Dynamics for Windowed Kinetic Data by Ileana Baldi, Corrado Lanera, Mohammad Junayed Bhuyan, Paola Berchialla, Luca Vedovelli, Dario Gregori

“…Conclusions: Monitoring food items using simple wristband-mounted wearable devices is feasible and accurate for some foods while unsatisfactory for others. Machine learning tools are necessary to deal with the complexity of signals gathered by the devices, and research is ongoing to improve accuracy further and work on large-scale and real-time implementation and testing.…”
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Machine learning cluster analysis identifies increased 12-month mortality risk in transcatheter aortic valve replacement recipients by Thomas Meredith, Thomas Meredith, Thomas Meredith, Farhan Mohammed, Amy Pomeroy, Sebastiano Barbieri, Sebastiano Barbieri, Erik Meijering, Louisa Jorm, David Roy, Jason Kovacic, Jason Kovacic, Jason Kovacic, Jason Kovacic, Michael Feneley, Michael Feneley, Michael Feneley, Christopher Hayward, Christopher Hayward, Christopher Hayward, David Muller, David Muller, David Muller, Mayooran Namasivayam, Mayooran Namasivayam, Mayooran Namasivayam

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Supporting clinical decision making in the emergency department for paediatric patients using machine learning: A scoping review protocol. by Fiona Leonard, Dympna O'Sullivan, John Gilligan, Nicola O'Shea, Michael J Barrett

“…<h4>Introduction</h4>Machine learning as a clinical decision support system tool has the potential to assist clinicians who must make complex and accurate medical decisions in fast paced environments such as the emergency department. …”
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Advancements and challenges in agriculture: a comprehensive review of machine learning and IoT applications in vertical farming and controlled environment agriculture by Binoy Sasmal, Gobinda Das, Preeti Mallick, Sneha Dey, Suman Ghorai, Subrata Jana, Chiranjibe Jana

“…Implementing VF will solve many challenges by utilizing modern machine learning, IoT, and AI techniques, increasing VF productivity and quality. …”
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Bond behavior of galvanized iron fiber reinforced concrete with recycled coarse aggregate and model prediction using machine learning by Md. Jahidul Islam, Ummul Wara Labiba, Tasfiah Faisal Chowdhury, Md. Shahjalal, Tanvir Mustafy, Tanvir Hassan Tusher

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Development of a Machine‐Learning Model for Diagnosis of Pancreatic Cancer from Serum Samples Analyzed by Thermal Liquid Biopsy by Sonia Hermoso‐Durán, Nicolas Fraunhoffer, Judith Millastre‐Bocos, Oscar Sanchez‐Gracia, Pablo F. Garrido, Sonia Vega, Ángel Lanas, Juan Iovanna, Adrián Velázquez‐Campoy, Olga Abian

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Determination of 5-fluorouracil anticancer drug solubility in supercritical CO 2 using semi-empirical and machine learning models by Gholamhossein Sodeifian, Ratna Surya Alwi, Reza Derakhsheshpour, Nedasadat Saadati Ardestani

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Investigation of groundwater quality indices and health risk assessment of water resources of Jiroft city, Iran, by machine learning algorithms by Sobhan Maleky, Maryam Faraji, Majid Hashemi, Akbar Esfandyari

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Prediction of football injuries using GPS-based data in Iranian professional football players: a machine learning approach by Reza Saberisani, Amir Hossein Barati, Mostafa Zarei, Paulo Santos, Armin Gorouhi, Luca Paolo Ardigò, Hadi Nobari

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Assessing Glioblastoma Treatment Response Using Machine Learning Approach Based on Magnetic Resonance Images Radiomics: An Exploratory Study by Amirreza Sadeghinasab, Jafar Fatahiasl, Marziyeh Tahmasbi, Sasan Razmjoo, Mohammad Yousefipour

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Unveiling farmers’ perceptions: a citizen science and machine learning approach to exploring drivers in the adequacy and fairness of water systems by Vasilios Plakandaras, Fahad Khan Khadim, Vassiliki Kazana, Emmanouil Anagnostou, Amvrossios C Bagtzoglou

Subjects: “…machine learning…”
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Automated Detection of Macular Diseases by Optical Coherence Tomography and Artificial Intelligence Machine Learning of Optical Coherence Tomography Images by Soichiro Kuwayama, Yuji Ayatsuka, Daisuke Yanagisono, Takaki Uta, Hideaki Usui, Aki Kato, Noriaki Takase, Yuichiro Ogura, Tsutomu Yasukawa

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Enhancing trauma triage in low-resource settings using machine learning: a performance comparison with the Kampala Trauma Score by Mike Nsubuga, Timothy Mwanje Kintu, Helen Please, Kelsey Stewart, Sergio M. Navarro

Subjects: “…Machine learning…”
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Bearing Response Prediction in Hydrothermal Aged Carbon Fiber Reinforced Epoxy Composite Joints Using Machine Learning Techniques by Mohit Kumar, Govind Vashishtha, Babita Dhiman, Sumika Chauhan

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Enhancing precision in multiple sclerosis lesion segmentation: A U-net based machine learning approach with data augmentation by Oezdemir Cetin, Berkay Canel, Gamze Dogali, Unal Sakoglu

“…This study proposes a robust machine learning algorithm designed to identify MS lesions using both single-modal and multi-modal MRI data. …”
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Diagnosis and prognosis of melanoma from dermoscopy images using machine learning and deep learning: a systematic literature review by Hoda Naseri, Ali A. Safaei

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