Machine Learning Applications in Cancer Prognosis and Prediction

Cited by (1,005)

Items 701–800 of 1,005

1. Machine Learning in Colorectal Cancer Risk Prediction from Routinely Collected Data: A Review
   Bruce Burnett, Shang‐Ming Zhou, Sinead T Brophy, Phil Davies, Paul Ellis, Jonathan Kennedy, Amrita Bandyopadhyay, Michael Parker, Ronan Anthony Lyons · 2023 · Diagnostics
2. Ancient dormant virus remnant ERVW-1 drives ferroptosis via degradation of GPX4 and SLC3A2 in schizophrenia
   Dong‐Yan Zhang, Xiulin Wu, Xing Xue, Wenshi Li, Ping Zhou, Zhao Lv, Kexin Zhao, Fan Zhu · 2023 · Virologica Sinica
3. Understanding the Bioinformatics Challenges of Integrating Genomics Into Healthcare
   Ahmad Al Kawam, Arun Sen, Aniruddha A. Datta, Nancy J. Dickey · 2017 · IEEE Journal of Biomedical and Health Informatics
4. Comparison of three data mining models for prediction of advanced schistosomiasis prognosis in the Hubei province
   Guo Li, Xiaorong Zhou, Jianbing Liu, Yuanqi Chen, Hengtao Zhang, Yanyan Chen, Jianhua Liu, Hongbo Jiang, Junjing Yang, Shaofa Nie · 2018 · PLoS neglected tropical diseases
5. Artificial Intelligence in Medicine and Radiation Oncology
   Vincent Weidlich, Georg A. Weidlich · 2018 · Cureus
6. Fusobacterium nucleatum modulates the Wnt/β-catenin pathway in colorectal cancer development
   Tanushree Mondal, Deepanjan Chattopadhyay, Paromita Saha Mondal, Sanjib Das, Amalesh Mondal, Abhishek Das, Subhasree Samanta, Tanima Saha · 2025 · International Journal of Biological Macromolecules
7. Advancement in public health through machine learning: a narrative review of opportunities and ethical considerations
   Sumit Singh Dhanda, Deepak Panwar, Chia‐Chen Lin, Tarun Kumar Sharma, Deependra Rastogi, Shantanu Bindewari, Anand Mohan Singh, Yung‐Hui Li, Neha Kumari Agarwal, Saurabh Agarwal · 2025 · Journal Of Big Data
8. Treatment Outcome Prediction for Cancer Patients Based on Radiomics and Belief Function Theory
   Jian Wu, Chunfeng Lian, Su Ruan, Thomas R. Mazur, Sasa Mutic, Mark A. Anastasio, Perry W. Grigsby, Pierre Véra, Hua Li · 2018 · IEEE Transactions on Radiation and Plasma Medical Sciences
9. Web-Application Development for Tasks of Prediction in Medical Domain
   Mariia S. Mazorchuk, Viktoriia Dobriak, Dmytro Chumachenko · 2018 · IEEE International Conference on Computer Sciences and Information Technologies (CSIT)
10. Value of pre-operative CTX serum levels in the prediction of medication-related osteonecrosis of the jaw (MRONJ): a retrospective clinical study
    Martin Salgueiro, Michael Stribos, Li Fang Zhang, Mark R. Stevens, Mohamed E. Awad, Mohammed E. Elsalanty · 2019 · The EPMA Journal
11. Identifying Vulnerable Households Using Machine Learning
    Chen Gao, Chengcheng J. Fei, Bruce A. McCarl, David J. Leatham · 2020 · Sustainability
12. Imaging Beyond Seeing: Early Prognosis of Cancer Treatment
    Changrong Shi, Zijian Zhou, Hongyu Lin, Jinhao Gao · 2020 · Small Methods
13. Cancer Prognosis Using Artificial Intelligence-Based Techniques
    Surbhi Gupta, Yogesh Kumar · 2021 · SN Computer Science
14. Application of artificial intelligence in a real-world research for predicting the risk of liver metastasis in T1 colorectal cancer
    Tenghui Han, Jun Wei Zhu, Xiaoping Chen, Rujie Chen, Yu Jiang, Shuai Wang, Dong Xu, Gang Shen, Jianyong Zheng, Chunsheng Xu · 2022 · Cancer Cell International
15. ExhauFS: exhaustive search-based feature selection for classification and survival regression
    Stepan A. Nersisyan, Victor Novosad, Alexei Vladimirovich Galatenko, Andrey Sokolov, Grigoriy V. Bokov, Alexander Konovalov, Dmitry Alekseev, Alexander Tonevitsky · 2022 · PeerJ
16. Analysis of risk factors associated with acute respiratory infections among under-five children in Uganda
    Yassin Nshimiyimana, Yingchun Zhou · 2022 · BMC Public Health
17. An artificial intelligence model to predict survival and chemotherapy benefits for gastric cancer patients after gastrectomy development and validation in international multicenter cohorts
    Xunjun Li, ZhongYa Zhai, Wenfu Ding, Li Chen, Yuyun Zhao, Wenjun Xiong, Yunfei Zhang, Dingyi Lin, Zequn Chen, Wei Wang et al. · 2022 · International Journal of Surgery
18. Machine-learning-based approach for nonunion prediction following osteoporotic vertebral fractures
    Shinji Takahashi, Hidetomi Terai, Masatoshi Hoshino, Tadao Tsujio, Minori Kato, Hiromitsu Toyoda, Akinobu Suzuki, Koji Tamai, Akito Yabu, Hiroaki Nakamura · 2022 · European Spine Journal
19. A multi-view co-training network for semi-supervised medical image-based prognostic prediction
    Hailin Li, Siwen Wang, Bo Liu, Mengjie Fang, Runnan Cao, Bingxi He, Shengyuan Liu, C. Y. Hu, Di Dong, Ximing Wang et al. · 2023 · Neural Networks
20. Modeling the survival of colorectal cancer patients based on colonoscopic features in a feature ensemble vision transformer
    Chung‐Ming Lo, Yi-Wen Yang, Jen‐Kou Lin, Wei‐Shone Chen, Wei-Shone Chen, Shung-Haur Yang, Shih-Ching Chang, Huann-Sheng Wang, Yuan‐Tzu Lan, Hung-Hsin Lin et al. · 2023 · Computerized Medical Imaging and Graphics
21. DiffPrep: Differentiable Data Preprocessing Pipeline Search for Learning over Tabular Data
    Peng Li, Zhiyi Chen, Xu Chu, Kexin Rong · 2023 · Proceedings of the ACM on Management of Data
22. On the Robustness of Random Forest Against Untargeted Data Poisoning: An Ensemble-Based Approach
    Marco Anisetti, Claudio A. Ardagna, Alessandro Balestrucci, Nicola Bena, Ernesto Damiani, Chan Yeob Yeun · 2023 · IEEE Transactions on Sustainable Computing
23. Artificial intelligence applications in pediatric oncology diagnosis
    Yuhan Yang, Yimao Zhang, Yuan Li · 2023 · Exploration of Targeted Anti-tumor Therapy
24. Machine learning in onco-pharmacogenomics: a path to precision medicine with many challenges
    Alessia Mondello, Michele Dal Bo, Giuseppe Toffoli, Maurizio Polano · 2024 · Frontiers in Pharmacology
25. Enhancing digital health services: A machine learning approach to personalized exercise goal setting
    Ji Fang, Vincent C. S. Lee, Hao Ji, Haiyan Wang · 2024 · Digital Health
26. Integrating machine learning driven virtual screening and molecular dynamics simulations to identify potential inhibitors targeting PARP1 against prostate cancer
    Fahad M. Aldakheel, Shatha Ahmed Alduraywish, Khaled H. Dabwan · 2025 · Scientific Reports
27. Deconstructing the ethics of large language models from long-standing issues to new-emerging dilemmas: a survey
    Chengyuan Deng, Yiqun Duan, Xin Jin, Heng Chang, Yijun Tian, Han Liu, Yi‐Chen Wang, Kuofeng Gao, Henry Peng Zou, Yiqiao Jin et al. · 2025 · AI and Ethics
28. Automatic Ontology Construction Using Text Corpora and Ontology Design Patterns (ODPs) in Alzheimer’s Disease
    Denis Eka Cahyani, Ito Wasito · 2017 · Jurnal Ilmu Komputer dan Informasi
29. Immune mediator expression signatures are associated with improved outcome in ovarian carcinoma
    Mano Nakamura, Heather J. Bax, Daniele Scotto, Elmira Amiri Souri, Sam Sollie, R. J. C. Harris, Niklas Hammar, Göran Walldius, A. Winship, Sharmistha Ghosh et al. · 2019 · OncoImmunology
30. Multi-Objective Optimization for Personalized Prediction of Venous Thromboembolism in Ovarian Cancer Patients
    Maria Emilia Fresard, Rafaela Erices, María Loreto Bravo, Mauricio A. Cuello, Gareth I. Owen, Carolina Ibáñez, María Rodriguez-Fernández · 2019 · IEEE Journal of Biomedical and Health Informatics
31. Survey of Machine Learning Techniques in Medical Imaging
    Munya A. Arasi · 2019 · International Journal of Advanced Trends in Computer Science and Engineering
32. Derivation and Application of Molecular Signatures to Prostate Cancer: Opportunities and Challenges
    Dimitrios Doultsinos, Ian Geoffrey Mills · 2021 · Cancers
33. Gene selection and classification of microarray gene expression data based on a new adaptive L1-norm elastic net penalty
    Aiedh Mrisi Alharthi, Muhammad Hisyam Lee, Zakariya Yahya Algamal · 2021 · Informatics in Medicine Unlocked
34. Identifying novel transcript biomarkers for hepatocellular carcinoma (HCC) using RNA-Seq datasets and machine learning
    Rajinder Gupta, Jos C. S. Kleinjans, Florian Caiment · 2021 · BMC Cancer
35. A Novel Multi-Neural Ensemble Approach for Cancer Diagnosis
    Surbhi Gupta, Manoj Kumar Gupta, Rakesh Kumar · 2021 · Applied Artificial Intelligence
36. Random survival forest model identifies novel biomarkers of event-free survival in high-risk pediatric acute lymphoblastic leukemia
    Zachary S. Bohannan, Frederick D. Coffman, Antonina Mitrofanova · 2022 · Computational and Structural Biotechnology Journal
37. Artificial intelligence and imaging for risk prediction of pancreatic cancer: a narrative review
    Touseef Ahmad Qureshi, Sehrish Javed, Tabasom Sarmadi, Stephen Jacob Pandol, Debiao Li · 2022 · Chinese Clinical Oncology
38. Fake Profile Identification in Social Network using Machine Learning and NLP
    P Latha, V. Sumitra, V. Sasikala, J. Arunarasi, A. R. Rajini, N. Nithiya · 2022 · International Conference on Communication, Computing and Internet of Things (IC3IoT)
39. A review on Natural Language Processing Models for COVID-19 research
    Karl Hall, Victor I. C. Chang, Chrisina Jayne · 2022 · Healthcare Analytics
40. Machine learning approaches in the diagnosis of infectious diseases: a review
    Smriti Mishra, Ranjan Kumar, Sanjay Tiwari, Priya Ranjan · 2022 · Bulletin of Electrical Engineering and Informatics
41. CJT-DEO: Condorcet’s Jury Theorem and Differential Evolution Optimization based ensemble of deep neural networks for pulmonary and Colorectal cancer classification
    Gaurav Kumar Srivastava, Aninditaa Chauhan, Nitesh Pradhan · 2022 · Applied Soft Computing
42. Prognosis Individualized: Survival predictions for WHO grade II and III gliomas with a machine learning-based web application
    Mert Karabacak, Pemla Jagtiani, Alejandro Carrasquilla, Isabelle M. Germano, Konstantinos D. Margetis · 2023 · npj Digital Medicine
43. The Immune Landscape of Pheochromocytoma and Paraganglioma: Current Advances and Perspectives
    Ondřej Uher, Katerina Hadrava Vanova, David Taïeb, Bruna Calsina, Mercedes Robledo, Roderick John Clifton-Bligh, Karel Pacák · 2024 · Endocrine Reviews
44. High-Grade Serous Ovarian Cancer: Use of Machine Learning to Predict Abdominopelvic Recurrence on CT on the Basis of Serial Cancer Antigen 125 Levels
    Atul Bhanudas Shinagare, Patricia Balthazar, Ivan K. Ip, Ronilda C. Lacson, Joyce F. Liu, Nikhil H. Ramaiya, Ramin Khorasani · 2018 · Journal of the American College of Radiology
45. Identifying Protein Features Responsible for Improved Drug Repurposing Accuracies Using the CANDO Platform: Implications for Drug Design
    William Mangione, Ram Samudrala · 2019 · Molecules
46. Label‐only membership inference attacks on machine unlearning without dependence of posteriors
    Zhaobo Lu, Hai Liang, Minghao Zhao, Qingzhe Lv, Tiancai Liang, Yilei Wang · 2022 · International Journal of Intelligent Systems
47. Clinical decision support tool for breast cancer recurrence prediction using SHAP value in cooperative game theory
    Ying Liu, Yating Fu, Yadong Peng, Jie Ming · 2024 · Heliyon
48. A Machine Learning Model to Predict Risk for Hepatocellular Carcinoma in Patients With Metabolic Dysfunction-Associated Steatotic Liver Disease
    Souvik Sarkar, Aniket Alurwar, Carole Ly, Cindy Piao, Rajiv Donde, Christopher J. Wang, Frederick J. Meyers · 2024 · Gastro Hep Advances
49. Prediction of local site influence on seismic vulnerability using machine learning: A study of the 6 February 2023 Türkiye earthquakes
    Mustafa Şenkaya, Ali Silahtar, Enes Furkan Erkan, Hasan Karaaslan · 2024 · Engineering Geology
50. Artificial intelligence in breast cancer survival prediction: a comprehensive systematic review and meta-analysis
    Zohreh Javanmard, Saba Zarean Shahraki, Kosar Safari, Abbas Omidi, Sadaf Raoufi, Mahsa Rajabi, Mohammad Esmaeil Akbari, Mehrad Aria · 2025 · Frontiers in Oncology
51. Identification of prognostic signature in cancer based on DNA methylation interaction network
    Wei‐Lin Hu, Xionghui Zhou · 2017 · BMC Medical Genomics
52. Gastroenterology Meets Machine Learning: Status Quo and Quo Vadis
    Amina Adadi, Safae Adadi, Mohammed Berrada · 2019 · Advances in Bioinformatics
53. Type-2 Fuzzy PCA Approach in Extracting Salient Features for Molecular Cancer Diagnostics and Prognostics
    Vikas Singh, Nishchal Kumar Verma, Yan Cui · 2019 · IEEE Transactions on NanoBioscience
54. Estimating survival benefit of adjuvant therapy based on a Bayesian network prediction model in curatively resected advanced gallbladder adenocarcinoma
    Zhi-Min Geng, Zhi-Qiang Cai, Zhen Zhang, Zhaohui Tang, Feng Xue, Chen Chen, Dong Zhang, Qi Li, Rui Zhang, Wenzhi Li et al. · 2019 · World Journal of Gastroenterology
55. Cancer Diagnosis and Disease Gene Identification via Statistical Machine Learning
    Liuyuan Chen, Juntao Li, Mingming Chang · 2020 · Current Bioinformatics
56. Inteligencia artificial y aprendizaje automático en medicina
    Marianella Álvarez Vega, Laura María Quirós Mora, Mónica Valeria Cortés Badilla · 2020 · Revista Medica Sinergia
57. Breast cancer risk assessment and early diagnosis using Principal Component Analysis and support vector machine techniques
    Boluwaji Ade Akinnuwesi, Babafemi Oluropo Macaulay, Benjamin S. Aribisala · 2020 · Informatics in Medicine Unlocked
58. Research on the improvement of teachers’ teaching ability based on machine learning and digital twin technology
    Chen Siyan, Wang Ting-huai, Xiaomei Li, Zhu Liu, WU Dan-ying · 2020 · Journal of Intelligent & Fuzzy Systems
59. Is Machine Learning Revolutionizing Supply Chain?
    Mohamed-Iliasse Mahraz, Loubna Benabbou, Abdelaziz Berrado · 2020 · International Conference on Logistics Operations Management (GOL)
60. Analysis and Prediction Of Pima Indian Diabetes Dataset Using SDKNN Classifier Technique
    Radhanath Patra, Bonomali Khuntia · 2021 · IOP Conference Series Materials Science and Engineering
61. Identification of novel autoantibody signatures and evaluation of a panel of autoantibodies in breast cancer
    Cuipeng Qiu, Bofei Wang, Peng Wang, Xiao Wang, Yan Ma, Liping Dai, Jianxiang Shi, Keyan Wang, Guiying Sun, Hua Ye et al. · 2021 · Cancer Science
62. Non-destructive quality monitoring of 3D printed tissue scaffolds via dielectric impedance spectroscopy and supervised machine learning
    Shohanuzzaman Shohan, Jordan Harm, Mahmud Hasan, Binil Starly, Rohan A. Shirwaiker · 2021 · Procedia Manufacturing
63. An English Network Teaching Method Supported by Artificial Intelligence Technology and WBIETS System
    Haibao Du · 2021 · Scientific Programming
64. A comparative performance of breast cancer classification using hyper-parameterized machine learning models
    Lomboy Kristoffersen Edward Mayce R., Rowell Hernandez · 2021 · International Journal of Advanced Technology and Engineering Exploration
65. Towards Multimodal Machine Learning Prediction of Individual Cognitive Evolution in Multiple Sclerosis
    Stijn Denissen, Oliver Y. Chén, Johan De Mey, Maarten De Vos, Jeroen Van Schependom, Diana Maria Sima, Guy Nagels · 2021 · Journal of Personalized Medicine
66. Oral cancer diagnostics: An overview
    Akhilanand Chaurasia, SAMAN ISHRAT ALAM, NAVIN SINGH · 2021 · National Journal of Maxillofacial Surgery
67. A comparative analysis of classifiers in cancer prediction using multiple data mining techniques
    Seyed Mohammad Jafar Jalali, Sérgio Moro, Mohammad Reza Mahmoudi, Keramat Allah Ghaffary, Mohsen Maleki, Aref Alidoostan · 2017 · International Journal of Business Intelligence and Systems Engineering
68. Advancement in Deep Learning Methods for Diagnosis and Prognosis of Cervical Cancer
    Pankaj Yadav, Akshat Gupta, Alisha Parveen, Abhishek Kumar · 2022 · Current Genomics
69. Edge-Computing and Machine-Learning-Based Framework for Software Sensor Development
    Pál Péter Hanzelik, Alex Kummer, János Abonyi · 2022 · Sensors
70. Machine learning in point-of-care automated classification of oral potentially malignant and malignant disorders: a systematic review and meta-analysis
    Ashley Ferro, Sanjeev Kotecha, Kathleen Fan · 2022 · Scientific Reports
71. Real-time classification for Φ-OTDR vibration events in the case of small sample size datasets
    Nachuan Yang, Yongjun Zhao, Jinyang Chen, Fuqiang Wang · 2023 · Optical Fiber Technology
72. The innovative model based on artificial intelligence algorithms to predict recurrence risk of patients with postoperative breast cancer
    Lixuan Zeng, Lei Liu, Dongxin Chen, Henghui Lu, Xue Yang, Hongjie Bi, Weiwei Yang · 2023 · Frontiers in Oncology
73. Development of prediction models for one-year brain tumour survival using machine learning: a comparison of accuracy and interpretability
    Colleen E. Charlton, Michael T. C. Poon, Paul Martin Brennan, Jacques Fleuriot · 2023 · Computer Methods and Programs in Biomedicine
74. An Informative Review of Radiomics Studies on Cancer Imaging: The Main Findings, Challenges and Limitations of the Methodologies
    Roberta Fusco, Vincenza Granata, Igino Simonetti, Sergio Venanzio Setola, Maria Assunta Daniela Iasevoli, Filippo Tovecci, Ciro Michele Paolo Lamanna, Francesco Izzo, Biagio Pecori, Antonella Petrillo · 2024 · Current Oncology
75. Overconfidence is a Dangerous Thing: Mitigating Membership Inference Attacks by Enforcing Less Confident Prediction
    Zitao Chen, Karthik Pattabiraman · 2024 · Network and Distributed System Security Symposium
76. Statistical tools used for analyses of frequent users of emergency department: a scoping review
    Yohann Moanahere Chiu, François Racine-Hemmings, Isabelle Dufour, Alain Vanasse, Maud‐Christine Chouinard, Mathieu Bisson, Catherine Hudon · 2019 · BMJ Open
77. Towards more Accessible Precision Medicine: Building a more Transferable Machine Learning Model to Support Prognostic Decisions for Micro- and Macrovascular Complications of Type 2 Diabetes Mellitus
    Era Kim, Pedro J. Caraballo, M. Regina Castro, David S. Pieczkiewicz, György Simon · 2019 · Journal of Medical Systems
78. Amplification of the CD24 Gene Is an Independent Predictor for Poor Prognosis of Breast Cancer
    Peng Zhang, Pan Zheng, Yang Liu · 2019 · Frontiers in Genetics
79. Deep learning networks find unique mammographic differences in previous negative mammograms between interval and screen-detected cancers: a case-case study
    Benjamin Hinton, Lin Ma, Amir Pasha Mahmoudzadeh, Serghei Malkov, Bo Fan, Heather I. Greenwood, Bonnie N. Joe, Vivian Lee, Karla M. Kerlikowske, John A. Shepherd · 2019 · Cancer Imaging
80. Rider-chicken optimization dependent recurrent neural network for cancer detection and classification using gene expression data
    Chetan Nimba Aher, Ajay Kumar Jena · 2020 · Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization
81. Enhancing Health and Public Health through Machine Learning: Decision Support for Smarter Choices
    Pedro Miguel Rodrigues, João Paulo do Vale Madeiro, João Alexandre Lôbo Marques · 2023 · Bioengineering
82. Machine learning model to predict oncologic outcomes for drugs in randomized clinical trials
    Schperberg, Alexander V., Boichard, Amélie, Tsigelny, Igor F., Richard, Stéphane B., Kurzrock, Razelle · 2020 · International Journal of Cancer
83. The impact of AI on modern oncology from early detection to personalized cancer treatment
    Li, Jun, Zhang, Lei, Yu, Zhenglun, Bao, Zhiye, Li, Danyang, Wang, Liming · 2026 · npj Precision Oncology
84. A deep learning approach to improve built asset operations and disaster management in critical events: an integrative simulation model for quicker decision making
    Carlos Galera‐Zarco, Goulielmos Floros · 2023 · Annals of Operations Research
85. Applications of Machine Learning (ML) and Mathematical Modeling (MM) in Healthcare with Special Focus on Cancer Prognosis and Anticancer Therapy: Current Status and Challenges
    Jasmin Hassan, Safiya Mohammed Saeed, Lipika Deka, Md Jasim Uddin, Diganta Bhusan Das · 2024 · Pharmaceutics
86. Comparative Analysis of Shallow Learning and Deep Learning
    Ankita, Sonam Mittal, Ishu Sharma, Atul Kumar · 2023 · International Conference on Next Generation Electronics (NELEX)
87. Prediction of bio-oil yield by machine learning model based on 'enhanced data' training
    Chenxi Zhao, Xueying Lu, Zihao Jiang, Huan Ma, Juhui Chen, Xiaogang Liu · 2024 · Renewable Energy
88. A comparative study of methods for estimating model-agnostic Shapley value explanations
    Lars Henry Berge Olsen, Ingrid K. Glad, Martin Jullum, Kjersti Aas · 2024 · Data Mining and Knowledge Discovery
89. Advancements in Hyperspectral Imaging and Computer-Aided Diagnostic Methods for the Enhanced Detection and Diagnosis of Head and Neck Cancer
    I‐Chen Wu, Yen‐Chun Chen, Riya Karmakar, Arvind Mukundan, Gahiga Gabriel, Chih-Chiang Wang, Hsiang‐Chen Wang · 2024 · Biomedicines
90. Interleukin-6 Is a Crucial Factor in Shaping the Inflammatory Tumor Microenvironment in Ovarian Cancer and Determining Its Hot or Cold Nature with Diagnostic and Prognostic Utilities
    Hina Amer, Katie L. Flanagan, Nirmala Chandralega Kampan, Catherine Itsiopoulos, Clare L. Scott, Apriliana E. R. Kartikasari, Magdalena Plebanski · 2025 · Cancers
91. Microbiome-transcriptome-histology triad enhances survival risk stratification in multiple cancers
    Binsheng He, Yanyu Ma, Kun Wang, Pingping Bing, Lei Ji, Geng Tian, Haiyan Liu, Pingan He, Jialiang Yang · 2025 · Computational Biology and Chemistry
92. LncRNA ROR1‑AS1 high expression and its prognostic significance in liver cancer
    Ze Zhang, Shouqian Wang, Fan Yang, Zihui Meng, Yahui Liu · 2019 · Oncology Reports
93. A Crowdsourcing Framework for Medical Data Sets.
    Cheng Ye, Joseph Coco, Anna Epishova, Chen Hajaj, Henry Bogardus, Laurie Lovett Novak, Joshua C. Denny, Yevgeniy Vorobeychik, Thomas A. Lasko, Bradley Malin et al. · 2018 · Europe PMC (PubMed Central)
94. Machine learning in oncology: a review
    Cecilia Nardini · 2020 · ecancermedicalscience
95. Risk prediction for malignant intraductal papillary mucinous neoplasm of the pancreas: logistic regression versus machine learning
    Jae Seung Kang, Chanhee Lee, Wookyeong Song, Wonho Choo, Seungyeoun Lee, Sungyoung Lee, Youngmin Han, Claudio Bassi, Roberto Salvia, Giovanni Marchegiani et al. · 2020 · Scientific Reports
96. Classify multicategory outcome in patients with lung adenocarcinoma using clinical, transcriptomic and clinico-transcriptomic data: machine learning versus multinomial models
    Fei Deng, Lanlan Shen, He Wang, Lanjing Zhang · 2020 · PubMed Central
97. A Contemporary Machine Learning Method for Accurate Prediction of Cervical Cancer
    Jesse Jeremiah Tanimu, Mohamed Hamada, Mohammed Hassan, Saratu Yusuf Ilu · 2021 · SHS Web of Conferences
98. Systems biology informed neural networks (SBINN) predict response and novel combinations for PD-1 checkpoint blockade
    Michelle Przedborski, Munisha Smalley, Saravanan Thiyagarajan, Aaron J. Goldman, Mohammad Kohandel · 2021 · Communications Biology
99. Development and validation of a novel predictive model and web calculator for evaluating transfusion risk after spinal fusion for spinal tuberculosis: a retrospective cohort study
    Shengtao Dong, Wenle Li, Zhi‐Ri Tang, Haosheng Wang, Hao Pei, Bo Yuan · 2021 · BMC Musculoskeletal Disorders
100. Diagnosis of Gastric Cancer Using Machine Learning Techniques in Healthcare Sector: A Survey
     Danish Jamil, Sellappan Palaniappan, Asiah Lokman, Muhammad Naseem, Syed Saood Zia · 2022 · Informatica