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Toplam kayıt 48, listelenen: 41-48
Machine learning-based analysis of glioma grades reveals co-enrichment
(MDPI, 2022)
Gliomas develop and grow in the brain and central nervous system. Examining glioma grading processes is valuable for improving therapeutic challenges. One of the most extensive repositories storing transcriptomics data for ...
Transforming urinary stone disease management by artificial intelligence-based methods: A comprehensive review
(Elsevier, 2023)
Objective: To provide a comprehensive review on the existing research and evi-dence regarding artificial intelligence (AI) applications in the assessment and management of urinary stone disease.Methods: A comprehensive ...
Discovering the chemical factors behind regional royal jelly differences via machine learning
(Bursa Uludag University, 2023)
This study aims to discover the characteristic chemical factors for determining the region of royal jelly using machine learning. 84 samples from 13 different regions of Turkey were used for the study, and the chemical ...
MCNN-LSTM: Combining CNN and LSTM to classify multi-class text in imbalanced news data
(Institute of Electrical and Electronics Engineers Inc., 2023)
Searching, retrieving, and arranging text in ever-larger document collections necessitate more efficient information processing algorithms. Document categorization is a crucial component of various information processing ...
Exploring gene expression and clinical data for identifying prostate cancer severity levels using machine learning methods
(Institute of Electrical and Electronics Engineers Inc., 2023)
Prostate cancer (PCa) is the most common type of cancer in men worldwide. It is a cancer that starts in the small walnut-shaped male gland called the prostate. From the prostate, it can form a metastasis into other organs. ...
Automated analysis of the EEG signals for prediction of possible effectiveness of rTMS treatment in alzheimer's patient
(Institute of Electrical and Electronics Engineers Inc., 2022)
Alzheimer's disease (AD) is a progressive, chronic neurodegenerative brain disease that generally infects the elderly. The analysis of electroencephalography (EEG) signals has been commonly used for diagnosis. Repetitive ...
Non-cryptographic privacy preserving machine learning methods: a review
(Springer Science and Business Media Deutschland GmbH, 2024)
In recent years, the use of Machine Learning (ML) techniques to exploit data and produce predictive models has become widespread in decision-making and problem-solving across various fields, including healthcare, energy, ...
Secure future healthcare applications through federated learning approaches
(Springer Science and Business Media Deutschland GmbH, 2024)
The healthcare field is so sensitive to data privacy and security due to including medical and personal information. Almost all healthcare applications are required to increase data security and privacy, which use traditional ...