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A new report from the Medical College of Wisconsin discusses the development of a radiomic fingerprint for progression-free survival in cervical cancer. The study analyzed data from cervical cancer patients who underwent chemoradiation followed by MRI-based brachytherapy. Radiomic features extracted from MRI scans were analyzed, and support vector machine models were used to assess their association with progression-free survival. The study found promising evidence that radiomics metrics are associated with progression-free survival in cervical cancer. [Extracted from the article]

A recent study conducted by researchers at Laval University in Quebec City, Canada, explored the use of artificial intelligence (AI) in predicting the bulk density of dehydrated food products. The study compared three machine learning techniques - extreme learning machine (ELM), support vector machine (SVM), and evolutionary polynomial regression (EPR) - and found that SVM had the highest accuracy, while EPR performed best in terms of both accuracy and simplicity. The developed equations can be used to predict bulk density and optimize dehydration processes without the need for costly and time-consuming experiments. The study also discussed the opportunities and limitations of AI. [Extracted from the article]

State:Texas, United States, North and Central America, Artificial Neural Networks, Edinburg, Ear Diseases and Conditions, Emerging Technologies, Health and Medicine, Hearing Diseases and Conditions, Hearing Disorders, Machine Learning, Nervous System Diseases and Conditions, Networks, Neural Networks, Neurologic Manifestations, Otolaryngology, Sensation Disorders, Support Vector Machines, Tinnitus, Vector Machines New Tinnitus Study Results from University of Texas Rio Grande Valley Described (Predicting the Outcomes of Internet-based Cognitive Behavioral Therapy for Tinnitus: Applications of Artificial Neural Network and Support Vector Machine) Keywords: Edinburg; State:Texas; United States; North and Central America; Artificial Neural Networks; Ear Diseases and Conditions; Emerging Technologies; Health and Medicine; Hearing Diseases and Conditions; Hearing Disorders; Machine Learning; Nervous System Diseases and Conditions; Networks; Neural Networks; Neurologic Manifestations; Otolaryngology; Sensation Disorders; Support Vector Machines; Tinnitus; Vector Machines EN Edinburg State:Texas United States North and Central America Artificial Neural Networks Ear Diseases and Conditions Emerging Technologies Health and Medicine Hearing Diseases and Conditions Hearing Disorders Machine Learning Nervous System Diseases and Conditions Networks Neural Networks Neurologic Manifestations Otolaryngology Sensation Disorders Support Vector Machines Tinnitus Vector Machines 2023 JAN 30 (NewsRx) -- By a News Reporter-Staff News Editor at Clinical Trials Week -- Investigators publish new report on Hearing Diseases and Conditions - Tinnitus. [Extracted from the article]