Abstract: Knowledge-based fuzzy clustering algorithms can integrate prior knowledge, constraints or expert experience into the clustering process, thereby improving the interpretability and accuracy ...

PCA and K-means clustering applied to Raman and PL imaging reveal structural defects in silicon wafers, enhancing understanding of optoelectronic performance.

Overview: Free YouTube channels provide structured playlists covering AI, ML, and analytics fundamentals.Practical coding demonstrations help build real-world d ...

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...

After several years of increased antitrust scrutiny involving pricing algorithms (and hundreds of presentations at antitrust conferences around the globe), the people who matter are finally starting ...

As the world races to build artificial superintelligence, one maverick bioengineer is testing how much unprogrammed intelligence may already be lurking in our simplest algorithms to determine whether ...

Family has always been important to those working in population genetics. When Sohini Ramachandran was a postdoc, the issue of relatives in a dataset causing inaccurate results was considered a major ...

How do the algorithms that populate our social media feeds actually work? In a piece for Time Magazine excerpted from his recent book Robin Hood Math, Noah Giansiracusa sheds light on the algorithms ...