Machine learning models using initial neuropsychological and neuropsychiatric clinical data accurately distinguished AD from bvFTD.

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

An analysis of 5 machine-learning algorithms identified predictors for moderate-to-severe cancer-related fatigue in patients with CRC undergoing chemotherapy.

Demand forecasting remains one of the most complex challenges in retail management. As consumer behavior evolves rapidly, traditional statistical models have struggled to interpret nonlinear, dynamic ...

Overview Kaggle projects provide real-world experience in AI and machine learning.Participants gain practical skills in NLP, computer vision, and predictive mod ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

I have come across various ways of defining Artificial Neural Networks (ANNs). Many of them miss a fundamental characteristic of theirs. An ANN is a machine learning model. Like all machine learning ...

CNN and random forest model to detect multiple faults in bifacial PV systems, including dust, shading, aging, and cracks. Using simulated I-V curves and a 180-day synthetic dataset, the model achieved ...

Download PDF More Formats on IMF eLibrary Order a Print Copy Create Citation Forecasting inflation has become a major challenge for central banks since 2020, due to supply chain disruptions and ...