Machine learning applications in cancer prognosis and prediction

Cited by (1,006)

Items 401–500 of 1,006

1. Externally validated and clinically useful machine learning algorithms to support patient-related decision-making in oncology: a scoping review
   Cleiton Ferreira dos Santos, Mário Amorim‐Lopes · 2025 · BMC Medical Research Methodology
2. Challenges and caveats of a multi-center retrospective radiomics study: an example of early treatment response assessment for NSCLC patients using FDG-PET/CT radiomics
   Janita E. van Timmeren, Sara Carvalho, Ralph T. H. Leijenaar, Esther G.C. Troost, Wouter van Elmpt, Dirk De Ruysscher, J P Muratet, Fabrice Denis, Tanja Schimek‐Jasch, Ursula Nestle et al. · 2019 · PLoS ONE
3. An Enhanced Ensemble Diagnosis of Cervical Cancer: A Pursuit of Machine Intelligence Towards Sustainable Health
   Qazi Mudassar Ilyas, Muneer Ahmad · 2021 · IEEE Access
4. Sample Preparation and Diagnostic Methods for a Variety of Settings: A Comprehensive Review
   Zach E. Nichols, Chris D. Geddes · 2021 · Molecules
5. Prediction of early-stage melanoma recurrence using clinical and histopathologic features
   Guihong Wan, Nga Nguyen, Feng Liu, Mia S. DeSimone, Bonnie W. Leung, Ahmad A. Rajeh, Michael Ryan Collier, Min Seok Choi, Munachimso Amadife, Kimberly Tang et al. · 2022 · npj Precision Oncology
6. Single-Cell Analysis and Classification according to Multiplexed Proteins via Microdroplet-Based Self-Driven Magnetic Surface-Enhanced Raman Spectroscopy Platforms Assisted with Machine Learning Algorithms
   Jiaqi Wang, Lili Cong, Wei Shi, Weiqing Xu, Shuping Xu · 2023 · Analytical Chemistry
7. Towards Ensemble Feature Selection for Lightweight Intrusion Detection in Resource-Constrained IoT Devices
   Mahawish Fatima, Osama M. Hussain Rehman, Ibrahim M. H. Rahman, Aisha Ajmal, Simon Jigwan Park · 2024 · Future Internet
8. Use of Non-invasive Parameters and Machine-Learning Algorithms for Predicting Future Risk of Type 2 Diabetes: A Retrospective Cohort Study of Health Data From Kuwait
   Bassam Farran, Rihab Al‐Wotayan, Hessa Alkandari, Dalia Al‐Abdulrazzaq, Arshad Mohamed Channanath, Thangavel Alphonse Thanaraj · 2019 · Frontiers in Endocrinology
9. Machine Learning-Aided Computational Study of Metal–Organic Frameworks for Sour Gas Sweetening
   Eun Hyun Cho, Xuepeng Deng, Changlong Zou, Li‐Chiang Lin · 2020 · The Journal of Physical Chemistry C
10. Learning Machine Learning with Personal Data Helps Stakeholders Ground Advocacy Arguments in Model Mechanics
    Register, Yim, Ko, Amy J. · 2020 · Proceedings of the 2020 ACM Conference on International Computing Education Research
11. Determining causal relationships in leadership research using Machine Learning: The powerful synergy of experiments and data science
    Lee, Allan, Inceoglu, Ilke, Hauser, Oliver, Greene, Michael · 2022 · The Leadership Quarterly
12. Estimating treatment effects with machine learning
    Kenneth John McConnell, Stephan Lindner · 2019 · Health Services Research
13. An enhanced soft-computing based strategy for efficient feature selection for timely breast cancer prediction: Wisconsin Diagnostic Breast Cancer dataset case
    Law Kumar Singh, Munish Khanna, Rekha Singh · 2024 · Multimedia Tools and Applications
14. Machine Learning Approach to Inpatient Violence Risk Assessment Using Routinely Collected Clinical Notes in Electronic Health Records
    Vincent Menger, Marco René Spruit, Roel van Est, Eline Nap, Floor E. Scheepers · 2019 · JAMA Network Open
15. Classification and Clustering Algorithms of Machine Learning with their Applications
    Ravinder Ahuja, Aakarsha Chug, Shaurya Gupta, Pratyush Ahuja, Shruti Kohli · 2019 · Studies in computational intelligence
16. Artificial Intelligence and Machine Learning in Cancer Research: A Systematic and Thematic Analysis of the Top 100 Cited Articles Indexed in Scopus Database
    Ibrahim Hussein Musa, Lukman Olalekan Afolabi, Ibrahim Zamit, Taha Hussein Musa, Hassan Hussein Musa, Andrew N. Tassang, Tosin Yinka Akintunde, Wei Li · 2022 · Cancer Control
17. CREDO: Efficient and privacy-preserving multi-level medical pre-diagnosis based on ML-kNN
    Dan Zhu, Hui Zhu, Ximeng Liu, Hui Li, Fengwei Wang, Hao Li, Dengguo Feng · 2019 · Information Sciences
18. Medical decision support system for cancer treatment in precision medicine in developing countries
    Genghua Yu, Zhigang Chen, Jia Wu, Yanlin Tan · 2021 · Expert Systems with Applications
19. Adaptive Diagnosis of Lung Cancer by Deep Learning Classification Using Wilcoxon Gain and Generator
    Ooruchintala Obulesu, Suresh Kallam, Gaurav Dhiman, Rizwan Patan, Kadiyala Ramana, Yaswanth Raparthi, Sandeep Kautish · 2021 · Journal of Healthcare Engineering · Retracted
20. FACH
    Mohsen Imani, Sahand Salamat, Saransh Gupta, Jiani Huang, Tajana Rosing · 2019 · Asia and South Pacific Design Automation Conference (ASP-DAC)
21. Developing a Novel Machine Learning-Based Classification Scheme for Predicting SPCs in Breast Cancer Survivors
    Chi‐Chang Chang, Ssu‐Han Chen · 2019 · Frontiers in Genetics
22. Development and Validation of a Deep Learning Radiomics Model Predicting Lymph Node Status in Operable Cervical Cancer
    Taotao Dong, Chun Yang, Baoxia Cui, Ting Zhang, Xiubin Sun, Kun Song, Linlin Wang, Beihua Kong, Xingsheng Yang · 2020 · Frontiers in Oncology
23. Classifying Melanoma Skin Lesions Using Convolutional Spiking Neural Networks With Unsupervised STDP Learning Rule
    Qian Zhou, Yan Hui Shi, Zhenghua Xu, Ruowei Qu, Guizhi Xu · 2020 · IEEE Access
24. Applying Serum Proteins and MicroRNA as Novel Biomarkers for Early-Stage Cervical Cancer Detection
    Shengye Du, Yinghui Zhao, Changyu Lv, Meiling Wei, Zheng Gao, Xianhua Meng · 2020 · Scientific Reports
25. Machine learning-based lifetime breast cancer risk reclassification compared with the BOADICEA model: impact on screening recommendations
    Chang Ming, Valeria Viassolo, Nicole M Probst-Hensch, Ivo D. Dinov, Pierre Olivier Chappuis, Maria C. Katapodi · 2020 · British Journal of Cancer
26. Comparative Analysis of Machine Learning Algorithms for Early Prediction of Diabetes Mellitus in Women
    Sumbal Malik, Saad Harous, Hesham El‐Sayed · 2020 · Lecture notes in networks and systems
27. Accelerated design of architectured ceramics with tunable thermal resistance via a hybrid machine learning and finite element approach
    Erfan Fatehi, Hamidreza Yazdani Sarvestani, Behnam Ashrafi, Abdol Hamid Akbarzadeh · 2021 · Materials & Design
28. Machine Learning–Based Short-Term Mortality Prediction Models for Patients With Cancer Using Electronic Health Record Data: Systematic Review and Critical Appraisal
    Sheng-Chieh Lu, Cai Xu, Chandler Nguyen, Yimin Geng, André Pfob, Chris J. Sidey-Gibbons · 2022 · JMIR Medical Informatics
29. Ethical Issues in Consent for the Reuse of Data in Health Data Platforms
    Alex McKeown, Miranda Jane Mourby, Paul J. Harrison, Sophie Walker, Mark Sheehan, Ilina Singh · 2021 · Science and Engineering Ethics
30. Review paper on research direction towards cancer prediction and prognosis using machine learning and deep learning models
    Nimmagadda Satyanarayana Murthy, Chaitanya Bethala · 2021 · Journal of Ambient Intelligence and Humanized Computing
31. The Different Faces of AI Ethics Across the World: A Principle-to-Practice Gap Analysis
    Lionel Nganyewou Tidjon, Foutse Khomh · 2022 · IEEE Transactions on Artificial Intelligence
32. The Deep Learning ResNet101 and Ensemble XGBoost Algorithm with Hyperparameters Optimization Accurately Predict the Lung Cancer
    Saghir Ahmed, Basit Raza, Lal Hussain, Amjad Yousef Aldweesh, Abdulfattah Omar, Mohammad Shahbaz Khan, Elsayed Tag Eldin, Muhammad Amin Nadim · 2023 · Applied Artificial Intelligence
33. The use of artificial intelligence tools in cancer detection compared to the traditional diagnostic imaging methods: An overview of the systematic reviews
    Helbert Eustáquio Cardoso da Silva, Gláucia Nize Martins Santos, André Ferreira Leite, Carla Ruffeil Moreira Mesquita, Paulo Tadeu de Souza Figueiredo, Cristine Miron Stefani, Nilce Santos de Melo · 2023 · PLoS ONE
34. A systematic review of artificial intelligence techniques for oral cancer detection
    C. Kavyashree, H S Vimala, J Shreyas · 2024 · Healthcare Analytics
35. A neural network based breast cancer prognosis model with PCA processed features
    Smita Jhajharia, Harish Varshney, Seema Verma, Rajesh Kumar · 2016 · International Conference on Advances in Computing, Communications and Informatics (ICACCI)
36. The history, current status, and possible future of precision mental health
    Robert J. DeRubeis · 2019 · Behaviour Research and Therapy
37. Accurate prediction of glucose concentration and identification of major contributing features from hardly distinguishable near-infrared spectroscopy
    Bitewulign Kassa Mekonnen, Webb Yang, Tung‐Han Hsieh, Shien‐Kuei Liaw, Fu-Liang Yang · 2020 · Biomedical Signal Processing and Control
38. Combination of loss functions for robust breast cancer prediction
    Hamideh Hajiabadi, Vahide Babaiyan, Davood Zabihzadeh, Moein Hajiabadi · 2020 · Computers & Electrical Engineering
39. A Review on Recent Progress in Machine Learning and Deep Learning Methods for Cancer Classification on Gene Expression Data
    Aina Umairah Mazlan, Noor Azida Sahabudin, Muhammad Akmal Remli, Nor Syahidatul Nadiah Ismail, Mohd Saberi Mohamad, Hui Wen Nies, Nor Bakiah Abd Warif · 2021 · Processes
40. Machine learning for optimized individual survival prediction in resectable upper gastrointestinal cancer
    Jin‐On Jung, Nerma Crnovrsanin, Naita Maren Wirsik, Henrik Nienhüser, Leila Peters, Felix Popp, A. Schulze, Martin Wagner, Beat Peter Müller-Stich, Markus Wolfgang Büchler et al. · 2022 · Journal of Cancer Research and Clinical Oncology
41. Performance of machine learning algorithms for lung cancer prediction: a comparative approach
    Satya Prakash Maurya, Pushpendra Singh Sisodia, Rahul Mishra, Devesh Pratap Singh · 2024 · Scientific Reports
42. Comparing different venous thromboembolism risk assessment machine learning models in Chinese patients
    Xin Wang, Yuqing Yang, Si‐Hua Liu, Xin‐Yu Hong, Xuefeng Sun, Juhong Shi · 2019 · Journal of Evaluation in Clinical Practice
43. Development of robust artificial neural networks for prediction of 5-year survival in bladder cancer
    Hriday P. Bhambhvani, Alvaro Zamora, Eugene Shkolyar, Kris B. Prado, Daniel R. Greenberg, Alex M. Kasman, Joseph C. Liao, Sumit Anil Shah, Sandy Srinivas, Eila Curlee Skinner et al. · 2020 · Urologic Oncology Seminars and Original Investigations
44. Breast Cancer Detection Using Particle Swarm Optimization and Decision Tree Machine Learning Technique
    Jesutofunmi Onaope Afolayan, Marion O. Adebiyi, Micheal Olaolu Arowolo, Chinmay Chakraborty, Ayodele Ariyo Adebiyi · 2022 · Springer eBooks
45. Assessment of vector-host-pathogen relationships using data mining and machine learning
    Diing D.M. Agany, Jose E. Pietri, Etienne Z. Gnimpiéba · 2020 · Computational and Structural Biotechnology Journal
46. Deep Learning-Based Prediction Model for Breast Cancer Recurrence Using Adjuvant Breast Cancer Cohort in Tertiary Cancer Center Registry
    Ji‐Yeon Kim, Yong‐Seok Lee, Jonghan Yu, Youngmin Park, Se Kyung Lee, Minyoung Lee, Jeong Eon Lee, Seok Won Kim, Seok Jin Nam, Yeon Hee Park et al. · 2021 · Frontiers in Oncology
47. Machine-learning-based predictions of imprinting quality using ensemble and non-linear regression algorithms
    Bita Yarahmadi, Seyed Majid Hashemianzadeh, Seyed Mohamadreza Milani Hosseini · 2023 · Scientific Reports
48. Artificial intelligence for classification and detection of oral mucosa lesions on photographs: a systematic review and meta-analysis
    Rata Rokhshad, Hossein Mohammad‐Rahimi, Jeffery B. Price, Reyhaneh Shoorgashti, Zahra Abbasiparashkouh, Mahdieh Esmaeili, Bita Sarfaraz, Arad Rokhshad, Saeed Reza Motamedian, Parisa Soltani et al. · 2024 · Clinical Oral Investigations
49. Identification of Acute Lymphoblastic Leukemia in Microscopic Blood Image Using Image Processing and Machine Learning Algorithms
    Subhash Rajpurohit, Sanket Patil, Nitu Choudhary, Shreya Gavasane, Pranali K. Kosamkar · 2018 · International Conference on Advances in Computing, Communications and Informatics (ICACCI)
50. Selecting the best machine learning algorithm to support the diagnosis of Non-Alcoholic Fatty Liver Disease: A meta learner study
    Paolo Sorino, Maria Gabriella Caruso, Giovanni Misciagna, Caterina Bonfiglio, Angelo Campanella, Antonella Mirizzi, Isabella Franco, Antonella Bianco, Claudia Buongiorno, Rosalba Liuzzi et al. · 2020 · PLoS ONE
51. Benchmark and application of unsupervised classification approaches for univariate data
    Maria El Abbassi, Jan Overbeck, Oliver Braun, Michel Calame, Herre S. J. van der Zant, Mickael Lucien Perrin · 2021 · Communications Physics
52. Deep GONet: self-explainable deep neural network based on Gene Ontology for phenotype prediction from gene expression data
    Victoria Bourgeais, Farida Zehraoui, Mohamed Ben Hamdoune, Blaise Hanczar · 2021 · BMC Bioinformatics
53. DeepBTS: Prediction of Recurrence-free Survival of Non-small Cell Lung Cancer Using a Time-binned Deep Neural Network
    Lee, Bora, Chun, Sang Hoon, Hong, Ji Hyung, Woo, In Sook, Kim, Seoree, Jeong, Joon Won, Kim, Jae Jun, Lee, Hyun Woo, Na, Sae Jung, Beck, Kyongmin Sarah et al. · 2020 · Scientific Reports
54. Machine Learning-Based Virtual Screening and Molecular Simulation Approaches Identified Novel Potential Inhibitors for Cancer Therapy
    Muhammad Shahab, Guojun Zheng, Abbas Khan, Dong‐Qing Wei, Alexander S. Novikov · 2023 · Biomedicines
55. A novel enhanced hybrid clinical decision support system for accurate breast cancer prediction
    Law Kumar Singh, Munish Khanna, Rekha Singh · 2023 · Measurement
56. Defining Glioblastoma Resectability Through the Wisdom of the Crowd: A Proof-of-Principle Study
    Adam M. Sonabend, Brad E. Zacharia, Michael Brendan Cloney, A. M. Sonabend, Christopher R. Showers, Victoria Ebiana, Matthew N. Nazarian, Kristin R. Swanson, Anne L. Baldock, Henry Brem et al. · 2016 · Neurosurgery
57. Dynamically prognosticating patients with hepatocellular carcinoma through survival paths mapping based on time-series data
    Lujun Shen, Qi Zeng, Pi Guo, Jingjun Huang, Chaofeng Li, Tao Pan, Boyang Chang, Nan Wu, Lewei Yang, Qifeng Chen et al. · 2018 · Nature Communications
58. Liquid biopsies for hepatocellular carcinoma
    Ying‐Hsiu Su, Amy K. Kim, Surbhi Jain · 2018 · Translational research
59. Enhancing the Performance of Classification Using Super Learning
    Md Faisal Kabir, Simone A. Ludwig · 2019 · Data-Enabled Discovery and Applications
60. Clinical validation of an immunohistochemistry‐based CanAssist‐Breast test for distant recurrence prediction in hormone receptor‐positive breast cancer patients
    Manjiri Manohar Bakre, Charusheila Ramkumar, Arun Kumar Attuluri, Chetana Basavaraj, Chandra Prakash, Ljubomir J. Buturović, Lekshmi Madhav, Nirupama Naidu, R Prathima, S. P. Somashekhar et al. · 2019 · Cancer Medicine
61. Prospecting (in) the data sciences
    Stephen C. Slota, Andrew S. Hoffman, David Ribes, Geoffrey C. Bowker · 2020 · Big Data & Society
62. KRAS, NRAS, and BRAF mutation prevalence, clinicopathological association, and their application in a predictive model in Mexican patients with metastatic colorectal cancer: A retrospective cohort study
    Héctor E. Sánchez-Ibarra, Xianli Jiang, Elena Yareli Gallegos-Gonzalez, Adriana Carolina Cavazos-González, Yenho Chen, Faruck Morcos, Hugo Alberto Barrera-Saldaña · 2020 · PLoS ONE
63. Predicting the Appearance of Hypotension during Hemodialysis Sessions Using Machine Learning Classifiers
    Juan Antonio Gomez-Pulido, Juan Antonio Gomez-Pulido, Diego Rodrı́guez-Puyol, María-Luz Polo-Luque, Miguel Vargas-Lombardo · 2021 · International Journal of Environmental Research and Public Health
64. The topology of data: opportunities for cancer research
    Ciara F. Loughrey, Padraig Fitzpatrick, Nick Orr, Anna Jurek · 2021 · Bioinformatics
65. Machine learning in medicine
    Gui, Chloe, Chan, Victoria · 2017 · University of Western Ontario Medical Journal
66. Artificial Intelligence in Differential Diagnostics of Meningitis: A Nationwide Study
    Alexios‐Fotios A. Mentis, Irene García, J Quero Jiménez, Maria Paparoupa, Athanasia Xirogianni, Anastasia Papandreou, Georgina Tzanakaki · 2021 · Diagnostics
67. The Ethics of AI in Health Care: A Mapping Review
    Jessica Morley, Caio C. Vieira Machado, Christopher Burr, Josh Cowls, Indra Joshi, Mariarosaria Taddeo, Luciano Floridi · 2020 · Philosophical studies series
68. Artificial intelligence for predicting survival following deceased donor liver transplantation: Retrospective multi-center study
    Young‐Dong Yu, Kwang-Sig Lee, Jong Man Kim, Je Ho Ryu, Jae Geun Lee, Kwang‐Woong Lee, Bong‐Wan Kim, Dong‐Sik Kim · 2022 · International Journal of Surgery
69. From Serendipity to Precision: Integrating AI, Multi-Omics, and Human-Specific Models for Personalized Neuropsychiatric Care
    Masaru Tanaka · 2025 · Biomedicines
70. Artificial intelligence-driven approaches in antibiotic stewardship programs and optimizing prescription practices: A systematic review
    Hamid Harandi, Maryam Shafaati, Mohammadreza Salehi, Mohammad Mahdi Roozbahani, Keyhan Mohammadi, Samaneh Akbarpour, Ramin Rahimnia, Gholamreza Hassanpour, Yasin Rahmani, Arash Seifi · 2025 · Artificial Intelligence in Medicine
71. Mining Prognosis Index of Brain Metastases Using Artificial Intelligence
    Shigao Huang, Jie Yang, Simon James Fong, Qi Zhao · 2019 · Cancers
72. Age Assessment of Youth and Young Adults Using Magnetic Resonance Imaging of the Knee: A Deep Learning Approach
    Ana Luiza Dallora, Johan Sanmartin Berglund, Martin Brogren, Ola Kvist, Sandra Díaz, André Dübbel, Peter Anderberg · 2019 · JMIR Medical Informatics
73. Using machine learning to predict early readmission following esophagectomy
    Siavash Bolourani, Mohammad A. Tayebi, Li Diao, Ping Wang, Vihas M Patel, Frank Manetta, Paul C. Lee · 2020 · Journal of Thoracic and Cardiovascular Surgery
74. A black-box adversarial attack for poisoning clustering
    Antonio Emanuele Ciná, Alessandro Torcinovich, Marcello Pelillo · 2021 · Pattern Recognition
75. A Review of Computer-Aided Expert Systems for Breast Cancer Diagnosis
    Xin Yu Liew, Nazia Hameed, Jérémie Clos · 2021 · Cancers
76. A Comparative Analysis of Deep Learning Approaches for Predicting Breast Cancer Survivability
    Surbhi Gupta, Manoj K. Gupta · 2021 · Archives of Computational Methods in Engineering
77. In-situ optimization of thermoset composite additive manufacturing via deep learning and computer vision
    William Jordan Wright, Joshua Darville, Nurçin Çelik, Hilmar Koerner, Emrah Çelik · 2022 · Additive manufacturing
78. Machine learning, IoT and 5G technologies for breast cancer studies: A review
    Havva Elif Saroğlu, Ibraheem Abdullah Mohammed Shayea, Bilal Saoud, Marwan Hadri Azmi, Ayman A. El‐Saleh, Sawsan Ali Saad, Mohammad Ahmed Alnakhli · 2024 · Alexandria Engineering Journal
79. Metabolomics and Integrative Omics for the Development of Thai Traditional Medicine
    Sakda Khoomrung, Kwanjeera Wanichthanarak, Intawat Nookaew, Onusa Thamsermsang, Patcharamon Seubnooch, Tawee Laohapand, Pravit Akarasereenont · 2017 · Frontiers in Pharmacology
80. Classification and Regression Tree Approach for Prediction of Potential Hazards of Urban Airborne Bacteria during Asian Dust Events
    Keunje Yoo, Hyunji Yoo, Jae Min Lee, Sudheer Kumar Shukla, Joonhong Park · 2018 · Scientific Reports
81. A new classification method of ancient Chinese ceramics based on machine learning and component analysis
    Heyang Sun, Miao Liu, Li Li, Lingtong Yan, Yue Zhou, Xiangqian Feng · 2019 · Ceramics International
82. Long short-term memory artificial neural network model for prediction of prostate cancer survival outcomes according to initial treatment strategy: development of an online decision-making support system
    Kyo Chul Koo, Kwang Suk Lee, Suah Kim, Choongki Min, Gyu Rang Min, Young Hwa Lee, Woong Kyu Han, Koon Ho Rha, Sung Joon Hong, Seung Choul Yang et al. · 2020 · World Journal of Urology
83. Classification models for Invasive Ductal Carcinoma Progression, based on gene expression data-trained supervised machine learning
    Shikha Roy, Rakesh Kumar, Vaibhav Mittal, Dinesh Kumar Gupta · 2020 · Scientific Reports
84. The ecology and evolution of wildlife cancers: Applications for management and conservation
    Rodrigo Hamede, Rachel S. Owen, Hannah V. T. Siddle, Sarah Peck, Menna E. Jones, Antoine Marie Dujon, Mathieu Giraudeau, Benjamín Roche, Beáta Újvári, Frédéric Thomas A · 2020 · Evolutionary Applications
85. Feasibility of multi-parametric magnetic resonance imaging combined with machine learning in the assessment of necrosis of osteosarcoma after neoadjuvant chemotherapy: a preliminary study
    Bingsheng Huang, Jifei Wang, Meili Sun, Xin Chen, Danyang Xu, Zi-Ping Li, Jinting Ma, Shi‐Ting Feng, Zhenhua Gao · 2020 · BMC Cancer
86. Autoencoded DNA methylation data to predict breast cancer recurrence: Machine learning models and gene-weight significance
    Laura Macías‐García, M. Martínez-Ballesteros, José María Luna-Romera, José Manuel García-Heredia, Jorge García–Gutiérrez, José C. Riquelme · 2020 · Artificial Intelligence in Medicine
87. Machine Learning for Breast Cancer Classification With ANN and Decision Tree
    Reetodeep Hazra, Megha Banerjee, Leonardo Badia · 2020 · IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)
88. Single-Cell Clustering Based on Shared Nearest Neighbor and Graph Partitioning
    Xiaoshu Zhu, Jie Zhang, Yunpei Xu, Jianxin Wang, Xiaoqing Peng, Hong‐Dong Li · 2020 · Interdisciplinary Sciences Computational Life Sciences
89. A novel hybridized feature selection strategy for the effective prediction of glaucoma in retinal fundus images
    Law Kumar Singh, Munish Khanna, Shankar Thawkar, Rekha Singh · 2023 · Multimedia Tools and Applications
90. Artificial intelligence and allied subsets in early detection and preclusion of gynecological cancers
    Pankaj Kumar Garg, Atish Ranjan Mohanty, Sravani Keerthi Ramisetty, Prakash Kulkarni, David A. Horne, Evan P. Pisick, Ravi Salgia, Sharad S. Singhal · 2023 · Biochimica et Biophysica Acta (BBA) - Reviews on Cancer
91. Nuclear proliferomics: A new field of study to identify signatures of nuclear materials as demonstrated on alpha-UO3
    Ian J. Schwerdt, Alexandria Brenkmann, Sean P. Martinson, Brent D. Albrecht, Sean Heffernan, Michael R. Klosterman, Trenton Kirkham, Tolga Taşdizen, Luther W. McDonald · 2018 · Talanta
92. An Ensemble Model for Breast Cancer Prediction Using Sequential Least Squares Programming Method (SLSQP)
    Madhuri Gupta, Bharat Gupta · 2018 · International Conference on Contemporary Computing
93. Big Data Analytics and Sensor-Enhanced Activity Management to Improve Effectiveness and Efficiency of Outpatient Medical Rehabilitation
    Mike Jones, George Collier, David J. Reinkensmeyer, Frank DeRuyter, John Dzivak, Daniel K. Zondervan, John Morris · 2020 · International Journal of Environmental Research and Public Health
94. Power Prediction of Airborne Wind Energy Systems Using Multivariate Machine Learning
    Mostafa A. Rushdi, Ahmad Rushdi, Tarek Naem Dief, Amr M. Halawa, Shigeo Yoshida, Roland Schmehl · 2020 · Energies
95. A Cancer Biologist's Primer on Machine Learning Applications in High‐Dimensional Cytometry
    Timothy Keyes, Pablo Domizi, Yu‐Chen Lo, Garry P. Nolan, Kara Lynn Davis · 2020 · Cytometry Part A
96. Integrative survival analysis of breast cancer with gene expression and DNA methylation data
    Isabelle Bichindaritz, Guanghui Liu, Christopher Bartlett · 2021 · Bioinformatics
97. Classification of adult autistic spectrum disorder using machine learning approach
    Nurul Amirah Mashudi, Norulhusna Binti Ahmad, Norliza Mohd Noor · 2021 · IAES International Journal of Artificial Intelligence
98. Survival prognostic factors in patients with acute myeloid leukemia using machine learning techniques
    Keyvan Karami, Mahboubeh Akbari, Mohammad‐Taher Moradi, Bijan Soleymani, Hossein Fallahi · 2021 · PLoS ONE
99. CHAIMELEON Project: Creation of a Pan-European Repository of Health Imaging Data for the Development of AI-Powered Cancer Management Tools
    Luis Martí‐Bonmatí, Ana Miguel, A. Suárez‐García, Mario Aznar, Jean-Paul Bérégi, Laure S Fournier, Emanuele Neri, Andrea Laghi, Manuela França, Francesco Sardanelli et al. · 2022 · Frontiers in Oncology
100. Artificial Intelligence Based on Blood Biomarkers Including CTCs Predicts Outcomes in Epithelial Ovarian Cancer: A Prospective Study
     Jun Ma, Jiani Yang, Yue Jin, Shanshan Cheng, Shan Huang, Nan Zhang, Yu Wang · 2021 · OncoTargets and Therapy