Default and optimized parameters for each predictive model. by Emily S. Nichols (8740029)

Schematic representation of semi-automated algorithm for organoids analyzing. by Anna Demchenko (18449439)

Personal recommendations of potassium and phosphorous intake () based on cross-validation predictions of nutrition effects, . Other parameters of the figure are similar to in-sampl... by Jari Turkia (17912475)

DataSheet1_Evolutionary algorithm for the optimization of meal intake and insulin administration in patients with type 2 diabetes.PDF by Eva Gonzalez-Flo (5046737)

Table 1_Association between pro-inflammatory diet and fecal incontinence: a large population-based study.pdf by Haiyang Wang (22389)

“…Background<p>It is widely acknowledged that dietary habits play a pivotal role in maintaining optimal intestinal health. …”

Image 1_Association between pro-inflammatory diet and fecal incontinence: a large population-based study.pdf by Haiyang Wang (22389)

“…Background<p>It is widely acknowledged that dietary habits play a pivotal role in maintaining optimal intestinal health. …”

Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment by Jianfang Cao (1881379)

“…The MapReduce parallel programming model on the Hadoop platform is used to perform an adaptive fusion of hue, local binary pattern (LBP) and scale-invariant feature transform (SIFT) features extracted from images to derive optimal combinations of weights. …”

Supplementary Material for: Development of an explainable machine learning model for cardiovascular-kidney-metabolic syndrome prediction based on dietary antioxidants in a national... by figshare admin karger (2628495)

“…We aimed to develop and interpret a machine learning model to predict advanced CKM stages based on dietary antioxidant profiles. Methods: Data were analyzed from 10,257 adults aged >30 years in the NHANES 2007–2010 and 2017–2018 cycles. …”

Data Sheet 5_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.pdf 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 7_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.pdf 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 6_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.pdf 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 3_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.pdf 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_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.pdf 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 2_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.pdf 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 4_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.pdf 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_Bi-objective goal programming for balancing costs vs. nutritional adequacy.pdf by Melissa F. Koenen (14262764)

Data_Sheet_1_Bi-objective goal programming for balancing costs vs. nutritional adequacy.pdf by Melissa F. Koenen (14262764)

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)

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)