Applications of deep learning techniques for automated multiple sclerosis detection using magnetic resonance imaging: A review
Multiple Sclerosis (MS) is a type of brain disease which causes visual, sensory, and motor
problems for people with a detrimental effect on the functioning of the nervous system. In …
problems for people with a detrimental effect on the functioning of the nervous system. In …
A survey on deep learning in medical image analysis
Deep learning algorithms, in particular convolutional networks, have rapidly become a
methodology of choice for analyzing medical images. This paper reviews the major deep …
methodology of choice for analyzing medical images. This paper reviews the major deep …
Deep learning based brain tumor segmentation: a survey
Brain tumor segmentation is one of the most challenging problems in medical image
analysis. The goal of brain tumor segmentation is to generate accurate delineation of brain …
analysis. The goal of brain tumor segmentation is to generate accurate delineation of brain …
[HTML][HTML] Uncovering convolutional neural network decisions for diagnosing multiple sclerosis on conventional MRI using layer-wise relevance propagation
Abstract Machine learning-based imaging diagnostics has recently reached or even
surpassed the level of clinical experts in several clinical domains. However, classification …
surpassed the level of clinical experts in several clinical domains. However, classification …
Quantitative imaging of cancer in the postgenomic era: Radio (geno) mics, deep learning, and habitats
Although cancer often is referred to as “a disease of the genes,” it is indisputable that the
(epi) genetic properties of individual cancer cells are highly variable, even within the same …
(epi) genetic properties of individual cancer cells are highly variable, even within the same …
QNMF: A quantum neural network based multimodal fusion system for intelligent diagnosis
Z Qu, Y Li, P Tiwari - Information Fusion, 2023 - Elsevier
Abstract The Internet of Medical Things (IoMT) has emerged as a significant research area in
the medical field, enabling the transmission of various types of data to the cloud for analysis …
the medical field, enabling the transmission of various types of data to the cloud for analysis …
Multiple sclerosis diagnosis using machine learning and deep learning: challenges and opportunities
Multiple Sclerosis (MS) is a disease that impacts the central nervous system (CNS), which
can lead to brain, spinal cord, and optic nerve problems. A total of 2.8 million are estimated …
can lead to brain, spinal cord, and optic nerve problems. A total of 2.8 million are estimated …
Artificial intelligence and healthcare: Forecasting of medical bookings through multi-source time-series fusion
Abstract Nowadays, Artificial intelligence (AI), combined with the digitalization of healthcare,
can lead to substantial improvements in Patient Care, Disease Management, Hospital …
can lead to substantial improvements in Patient Care, Disease Management, Hospital …
Derin öğrenme modelleri ve uygulama alanlarına ilişkin bir derleme
F Doğan, İ Türkoğlu - Dicle Üniversitesi Mühendislik Fakültesi …, 2019 - dergipark.org.tr
Derin öğrenme makine öğreniminin bir koludur. Makine öğreniminin başlarından günümüze
kadar geçen süreçte yapay zekaya olan ilgi giderek artmış ve günümüzde en çok kullanılan …
kadar geçen süreçte yapay zekaya olan ilgi giderek artmış ve günümüzde en çok kullanılan …
Insights into computational drug repurposing for neurodegenerative disease
MD Paranjpe, A Taubes, M Sirota - Trends in pharmacological sciences, 2019 - cell.com
Computational drug repurposing has the ability to remarkably reduce drug development
time and cost in an era where these factors are prohibitively high. Several examples of …
time and cost in an era where these factors are prohibitively high. Several examples of …