Table 1_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.docx by Yuwen ShangGuan (22633190)

“…Dietary data were collected through 24-h dietary recalls, encompassing macronutrients, micronutrients, food processing classification (NOVA), and five dietary quality scores. …”

Data_Sheet_1_A Machine Learning Based Dose Prediction of Lutein Supplements for Individuals With Eye Fatigue.XLSX by Juntao Kan (432159)

Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf by Muhammad Awais (263096)

“…Next, a hybrid feature extraction approach is presented leveraging transfer learning from selected deep neural network models, InceptionV3 and DenseNet201, to extract comprehensive feature sets. To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …”

Data Sheet 1_Balancing trade-offs between nutritional quality, consumer acceptability and climate impact across a spectrum of chili con carne formulations: from plant-based to hybr... by Mari Wollmar (14066233)

Data Sheet 4_Balancing trade-offs between nutritional quality, consumer acceptability and climate impact across a spectrum of chili con carne formulations: from plant-based to hybr... by Mari Wollmar (14066233)

Data Sheet 3_Balancing trade-offs between nutritional quality, consumer acceptability and climate impact across a spectrum of chili con carne formulations: from plant-based to hybr... by Mari Wollmar (14066233)

Data Sheet 2_Balancing trade-offs between nutritional quality, consumer acceptability and climate impact across a spectrum of chili con carne formulations: from plant-based to hybr... by Mari Wollmar (14066233)

Nutritional strategies in the rehabilitation of musculoskeletal injuries in athletes: a systematic integrative review - PROTOCOL by Diego A. Bonilla (9086201)

“…Similar to previously published articles [2], the review methodology was enhanced by optimizing the stages of literature search, data evaluation and data analysis in order to systematize the review process and improve the scientific soundness according to recommendations given by Hopia et al. [3] and the PRISMA in Exercise, Rehabilitation, Sport Medicine and Sports Science (PERSiST) guidelines [4].  …”

Data_Sheet_1_Evaluation of nutritional status and clinical depression classification using an explainable machine learning method.docx by Payam Hosseinzadeh Kasani (13280397)

“…</p>Methods<p>This study aimed to determine the ability of machine learning-based decision support methods to identify the presence of depression using publicly available health data from the Korean National Health and Nutrition Examination Survey. …”

Image_1_Evaluation of nutritional status and clinical depression classification using an explainable machine learning method.JPEG by Payam Hosseinzadeh Kasani (13280397)

“…</p>Methods<p>This study aimed to determine the ability of machine learning-based decision support methods to identify the presence of depression using publicly available health data from the Korean National Health and Nutrition Examination Survey. …”

Image_2_Evaluation of nutritional status and clinical depression classification using an explainable machine learning method.JPEG by Payam Hosseinzadeh Kasani (13280397)

“…</p>Methods<p>This study aimed to determine the ability of machine learning-based decision support methods to identify the presence of depression using publicly available health data from the Korean National Health and Nutrition Examination Survey. …”