1 天前 - … machine learning algorithms to this dataset, we aim to develop a robust model
capable of accurately identifying and categorizing tweets related to children’s medical disorders. …

1 天前 - … Two reviews on artificial intelligence (AI) and ML highlighted that the heterogeneity
of current studies demonstrates the need for meticulous validation, strict reporting systems, …

1 天前 - … , poor living conditions, limited access to healthcare services, and the presence of
other … , Artificial Neural Network (ANN) is the most widely used in the field of machine learning …

2 天前 - … Soil, as the primary repository of trace elements in the ecological environment
system, plays a crucial role in ecosystem health. Heavy metals (HMs) in soil not only threaten …

2 天前 - … health outcomes. This research highlights the potential of combining machine
learning with healthcare to … of regular monitoring and early detection in preventative healthcare. …

2 天前 - … , has been proposed as an artificial neural network (ANN) and was inspired by
biological neural networks. Over time, artificial neural networks have undergone significant …

2 天前 - … The primary objective of this thesis is to showcase computational methodologies
for Radiogenomics and Digital Pathology. Radiogenomics seeks to establish connections …

2 天前 - … ML is an artificial intelligence technology. It is based on statistical and mathematical
methods so that the computer is able to learn from the data. In other words, increasing the …

2 天前 - … -4 from electronic health records (EHR) can achieve quality levels equivalent to
those written by resident physicians.Methods: At a psychiatric primary care center, we utilized …

2 天前 - … Large language models (LLMs) show considerable abilities in diagnostic reasoning,
outperforming previous artificial intelligence (AI) models as well as human physicians in …