Results 41 to 50 of about 11,852,880 (383)
Complex & Intelligent Systems, 2020 The single-valued neutrosophic set (SVNS) is a well-known model for handling uncertain and indeterminate information. Information measures such as distance measures, similarity measures and entropy measures are very useful tools to be used in many ...
Jiajia Chai +6 more
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Differences between human and machine perception in medical diagnosis [PDF]
Scientific Reports, 2020 Deep neural networks (DNNs) show promise in image-based medical diagnosis, but cannot be fully trusted since they can fail for reasons unrelated to underlying pathology.
Taro Makino +20 more
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Genetics Research, 2022 Objective. The current study aimed to compare the characteristics of chromosome abnormalities detected by conventional G-banding karyotyping, chromosome microarray analysis (CMA), or fluorescence in situ hybridization (FISH)/CNVplex analysis and further ...
Jin Wang +9 more
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ENSEMBLE METHODS FOR SOLVING PROBLEMS OF MEDICAL DIAGNOSIS
Известия Томского политехнического университета: Промышленная кибернетика, 2023 The authors proposed the consolidating method for analyzing series of observations based on a fitted model of a mixture of catalysts of the main components, which makes it possible to study any number of markers. Contrasting the longitudinal approach, it
Anastasia A. Grigoreva +2 more
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Artificial Neural Networks in Medical Diagnosis
International Journal of Research Publication and ReviewsArtificial neural networks are finding many uses in the medical diagnosis application. The goal of this paper is to evaluate artificial neural network in disease diagnosis. Two cases are studied.
Qeethara Al-Shayea
semanticscholar +1 more source
Lightweight CNN for accurate brain tumor detection from MRI with limited training data
Frontiers in MedicineAimThis study aims to develop a robust and lightweight deep learning model for early brain tumor detection using magnetic resonance imaging (MRI), particularly under constraints of limited data availability.
Awad Bin Naeem +9 more
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A Novel Ensemble Learning Paradigm for Medical Diagnosis With Imbalanced Data
IEEE Access, 2020 With the help of machine learning (ML) techniques, the possible errors made by the pathologists and physicians, such as those caused by inexperience, fatigue, stress and so on can be avoided, and the medical data can be examined in a shorter time and in ...
Na Liu +5 more
semanticscholar +1 more source
IEEE Access, 2023 In this study, we investigate a novel conception called complex interval-valued hesitant fuzzy set (CIvHFS) as the modification of some prevailing conceptions such as interval-valued complex fuzzy set (IvCFS) and interval-valued hesitant fuzzy set (IvHFS)
Haojun Fang +4 more
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Literary and documentary evidence for lay medical practice in the Roman Republic and Empire [PDF]
, 2016 The majority of surviving ancient medical literature was written by medical practitioners and produced for the purpose of ensuring the effective diagnosis and treatment of their patients, suggesting an audience of medical professionals ranging from ...
Draycott, Jane
core +1 more source
Migraine Diagnosis by Using Artificial Neural Networks and Decision Tree Techniques
Online Academic Journal of Information Technology, 2014 Computer supported studies in wide range of medical fields have been greatly expanded in recent years. Also, many medical organizations continue to build databases for different diseases.
Ziynet Pamuk +2 more
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