| For: | Arkoudis NA, Papadakos SP. Machine learning applications in healthcare clinical practice and research. World J Clin Cases 2025; 13(1): 99744 [PMID: 39764535 DOI: 10.12998/wjcc.v13.i1.99744] |
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| URL: | https://www.wjgnet.com/2307-8960/full/v13/i1/99744.htm |
| Number | Citing Articles |
| 1 |
Reza Rahutomo, Syafiie Syam, Rizal Ashari Nampira, Akhmad Syaifuddin. Important Roles of Artificial Intelligence Continuous Glucose Monitoring: A Systematic Literature Review. 2025 International Conference on Information Management and Technology (ICIMTech) 2025; : 782 doi: 10.1109/ICIMTech67074.2025.11265532
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| 2 |
Prokash Gogoi, J. Arul Valan. Homomorphic encryption for secure and scalable predictive healthcare analytics: a review and case study. Life Cycle Reliability and Safety Engineering 2026; doi: 10.1007/s41872-025-00389-4
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| 3 |
Farah Farzaneh, Amir Soltani, Fatemeh Dastyar, Marzieh Mohammadi, Maryam Sadat Hosseini. AI-Driven predictive modeling of cervical intraepithelial neoplasia severity: a comprehensive analysis with clinical adoption frameworks. BMC Cancer 2025; 25(1) doi: 10.1186/s12885-025-14974-4
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| 4 |
Abhinav Dahiya, Devvrat Raghuvanshi, Chhaya Sharma, Kamaldeep Joshi, Ashima Nehra, Archana Sharma, Radha Jangra, Parul Badhwar, Renu Tuteja, Sarvajeet S. Gill, Ritu Gill. Deep learning method for malaria parasite evaluation from microscopic blood smear. Artificial Intelligence in Medicine 2025; 163: 103114 doi: 10.1016/j.artmed.2025.103114
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| 5 |
Geeta Tiwari, Sanjeev Kumar, Neeraj Tiwari, Korhan Cengiz. Integrating AI With Haptic Systems for Smarter Healthcare Solutions. Advances in Computational Intelligence and Robotics 2025; : 27 doi: 10.4018/979-8-3373-2307-7.ch002
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| 6 |
Chih-Hao Shen, Ruei-Hao Huang, Yaw-Kuen Li, Ta-Wei Chu, Dee Pei. Using machine learning methods to investigate the role of volatile organic compounds in non-alcoholic fatty liver disease. Frontiers in Molecular Biosciences 2025; 12 doi: 10.3389/fmolb.2025.1631265
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| 7 |
M P Simina, Sebastian Terence, M M Anishin Raj. A Machine Learning Approach to Predict Knee Septic Arthritis Using Engineered Clinical Features. 2025 11th International Conference on Smart Computing and Communications (ICSCC) 2025; : 1 doi: 10.1109/ICSCC66177.2025.11233634
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| 8 |
Vedavyasa Gurla, S Bhargavi Latha. An Analysis of Kidney Disease Prediction and Diagnosis using Machine Learning Strategies. 2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES) 2024; : 1 doi: 10.1109/ICSES63760.2024.10910518
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| 9 |
Ali Imad Alabdalhussein, Mohammed Hasan Al-Khafaji, Peter Conboy, Hitesh Singhavi, Fahid Anwar, Mohammed Elkrim, Miss Hazel Busby-Earle, Oladejo Olaleye, Nakul Patel, Sundar Raj Lakshmiah, Phillip Ameerally, Manish Devendra Mair. Evaluating the accuracy of machine learning in predicting postoperative flap complications: A meta-analysis. Journal of Plastic, Reconstructive & Aesthetic Surgery 2025; 111: 23 doi: 10.1016/j.bjps.2025.09.029
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| 10 |
Gelila Yitageasu, Eyob Akalewold Alemu, Eshetu Abera Worede, Mitkie Tigabie, Lidetu Demoze. Machine learning-based prediction of household sanitation facility access in Sub-Saharan Africa: insights from DHS data (2012–2024). Archives of Public Health 2025; 83(1) doi: 10.1186/s13690-025-01780-4
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| 11 |
Qilin Liu, Zhuang Liang, Xiaoshuang Qi, Shuwen Yang, Binyang Fu, Hui Dong. Contrast-Enhanced CT-Based Deep Learning and Habitat Radiomics for Analysing the Predictive Capability for Oral Squamous Cell Carcinoma. International Dental Journal 2025; 75(5): 100914 doi: 10.1016/j.identj.2025.100914
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