ArticleMultimedia tools and applications2022
Machine learning and deep learning approach for medical image analysis: diagnosis to detection.
Article in Multimedia tools and applications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
85 citing papers in PubMed, 3 syntheses or guidelines pooled it, 324 citations in OpenAlex.
- Deep learning applications in osteosarcoma MRI: A systematic review of recent advances in AI-based osteosarcoma diagnosis.PloS one · 2026Pooled it
- Application of machine learning in measurement of ageing and geriatric diseases: a systematic review.BMC geriatrics · 2023Pooled it
- Diagnostic test accuracy of machine learning algorithms for the detection intracranial hemorrhage: a systematic review and meta-analysis study.Biomedical engineering online · 2023Pooled it
- Integration of Federated Learning and Blockchain in Health Care: Tutorial on Medical Data, Architectures, Privacy, Security, and Regulatory Compliance.Journal of medical Internet research · 2026Article
- Human Crystallin Variation and Cataract.Investigative ophthalmology & visual science · 2026Review
- Machine learning enhanced optical spectroscopy for breast cancer diagnosis: A review.Lasers in medical science · 2026Review
- Deep Learning-Based Prediction System for Surgical Difficulty in Rectal Cancer Patients Using MRI Pelvimetry.Yonsei medical journal · 2026Article
- Progress in machine learning-assisted medical imaging for osteoarthritis and osteoporosis diagnosis: a narrative review.Quantitative imaging in medicine and surgery · 2026Review
- Attentional semantic attack for enhancing adversarial samples transferability.Scientific reports · 2026Article
- Data-Driven Printability Modeling of Hydrogels for Precise Direct Ink Writing Based on Rheological Properties.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Use of Artificial Intelligence Model Associated with Masson's Trichrome Staining as a Predictor of Muscle Invasion in Bladder Cancer.International journal of molecular sciences · 2026Article
- Swin Transformer-based intelligent fracture classification and radiographic assessment to support clinical decision-making.BMC medical informatics and decision making · 2026Article
- An interpretable machine learning model for detecting vision-threatening diabetic retinopathy among patients with diabetic retinopathy: a web-based cross-sectional study.Frontiers in endocrinology · 2026Article
- Automated retinal disease classification using deep learning and AlexNet with statistical models analysis.PloS one · 2026Article
- Clinician-Centric Explainable Artificial Intelligence Framework for Medical Imaging Diagnostics: A Systematic Review.International journal of biomedical imaging · 2026Review
- Application of Artificial Intelligence in Stem Cells and Gene Therapy for Gynecological Cancers.Current stem cell research & therapy · 2026Review
- Deep learning-based differentiation of non-tuberculous mycobacterial lung disease and pulmonary tuberculosis using chest CT.Frontiers in medicine · 2026Article
- Early diagnosis and developmental outcome prediction of agenesis of the corpus callosum via an interpretable deep multimodal fusion model.Frontiers in neuroscience · 2026Article
- Artificial intelligence-assisted photodynamic diagnosis and photodynamic therapy against cancer.Frontiers in oncology · 2026Review
- Pattern and structural detection in grayscale images through the application of quantile graphs in higher-dimensional spaces.Scientific reports · 2025Article
25 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Computer-aided detection using Deep Learning (DL) and Machine Learning (ML) shows tremendous growth in the medical field. Medical images are considered as the actual origin of appropriate information required for diagnosis of disease. Detection of disease at the initial stage, using various modalities, is one of the most important factors to decrease mortality rate occurring due to cancer and tumors. Modalities help radiologists and doctors to study the internal structure of the detected disease for retrieving the required features. ML has limitations with the present modalities due to large amounts of data, whereas DL works efficiently with any amount of data. Hence, DL is considered as the enhanced technique of ML where ML uses the learning techniques and DL acquires details on how machines should react around people. DL uses a multilayered neural network to get more information about the used datasets. This study aims to present a systematic literature review related to applications of ML and DL for the detection along with classification of multiple diseases. A detailed analysis of 40 primary studies acquired from the well-known journals and conferences between Jan 2014-2022 was done. It provides an overview of different approaches based on ML and DL for the detection along with the classification of multiple diseases, modalities for medical imaging, tools and techniques used for the evaluation, description of datasets. Further, experiments are performed using MRI dataset to provide a comparative analysis of ML classifiers and DL models. This study will assist the healthcare community by enabling medical practitioners and researchers to choose an appropriate diagnosis technique for a given disease with reduced time and high accuracy.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.