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Diseases

Machine Learning Enhances Disease Classification through Symptom-Based Cluster Analysis

Researchers from Robert Gordon University, in Aberdeen, UK, have published a study exploring the intersection of machine learning and healthcare. The investigation aims to improve disease classification through symptom-based cluster analysis, leveraging unsupervised machine learning algorithms. The study integrates a Large Language Model (LLM), specifically OpenAI's Generative Pretrained

Attention deficit hyperactivity disorder

Camouflaging in ADHD: A Critical Examination of Theoretical Foundations and Construct Validity

As the understanding of attention-deficit/hyperactivity disorder (ADHD) evolves, researchers are increasingly exploring the concept of camouflaging, which has traditionally been associated with autism spectrum disorder. A new preprint abstract suggests that the notion of camouflaging in ADHD is theoretically and neurocognitively flawed, with motivational, computational, and measurement incompatibilities. The