Multimodal artificial intelligence-based pathogenomics improves survival prediction in oral squamous cell carcinoma … – Nature.com
Sung, H. et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 Countries. CA Cancer J. Clin. 71, 209249 (2021).
Article PubMed Google Scholar
Chen, S.-H., Hsiao, S.-Y., Chang, K.-Y. & Chang, J.-Y. New insights into oral squamous cell carcinoma: From clinical aspects to molecular tumorigenesis. Int J. Mol. Sci. 22, 2252 (2021).
Article CAS PubMed Central PubMed Google Scholar
Adrien, J., Bertolus, C., Gambotti, L., Mallet, A. & Baujat, B. Why are head and neck squamous cell carcinoma diagnosed so late? Influence of health care disparities and socio-economic factors. Oral Oncol. 50, 9097 (2014).
Article CAS PubMed Google Scholar
Gonzlez-Moles, M. ., Aguilar-Ruiz, M. & Ramos-Garca, P. Challenges in the early diagnosis of oral cancer, evidence gaps and strategies for improvement: A scoping review of systematic reviews. Cancers 14, 4967 (2022).
Article PubMed Central PubMed Google Scholar
Russo, D. et al. Development and validation of prognostic models for oral squamous cell carcinoma: A systematic review and appraisal of the literature. Cancers 13, 5755 (2021).
Article PubMed Central PubMed Google Scholar
Carreras-Torras, C. & Gay-Escoda, C. Techniques for early diagnosis of oral squamous cell carcinoma: Systematic review. Med. Oral. Patol. Oral. Cir. Bucal. 20, e305-315 (2015).
Article PubMed Central PubMed Google Scholar
Alabi, R. O. et al. Machine learning in oral squamous cell carcinoma: Current status, clinical concerns and prospects for future-A systematic review. Artif. Intell. Med. 115, 102060 (2021).
Article PubMed Google Scholar
Qiu L, Khormali A, & Liu K. Deep Biological Pathway Informed Pathology-Genomic Multimodal Survival Prediction. (2023) [cited 2023 Apr 3]; https://arxiv.org/abs/2301.02383
Vale-Silva, L. A. & Rohr, K. Long-term cancer survival prediction using multimodal deep learning. Sci. Rep. 11, 13505 (2021).
Article CAS PubMed Central ADS PubMed Google Scholar
Carrillo-Perez, F. et al. Machine-learning-based late fusion on multi-omics and multi-scale data for non-small-cell lung cancer diagnosis. JPM 12, 601 (2022).
Article PubMed Central PubMed Google Scholar
Lipkova, J. et al. Artificial intelligence for multimodal data integration in oncology. Cancer Cell. 40, 10951110 (2022).
Article CAS PubMed Central PubMed Google Scholar
Steyaert, S. et al. Multimodal deep learning to predict prognosis in adult and pediatric brain tumors. Commun. Med. 3, 44 (2023).
Article PubMed Central PubMed Google Scholar
Saravi, B. et al. Artificial intelligence-driven prediction modeling and decision making in spine surgery using hybrid machine learning models. J. Personal. Med. 12, 509 (2022).
Article Google Scholar
Zuley, M.L., Jarosz, R., Kirk, S., Lee, Y., Colen, R., & Garcia, K., et al. The Cancer Genome Atlas Head-Neck Squamous Cell Carcinoma Collection (TCGA-HNSC), The Cancer Imaging Archive, 2016 (Accessed 3 Apr 2023); https://wiki.cancerimagingarchive.net/x/VYG0
Li, X. et al. Multi-omics analysis reveals prognostic and therapeutic value of cuproptosis-related lncRNAs in oral squamous cell carcinoma. Front. Genet. 13, 984911 (2022).
Article CAS PubMed Central PubMed Google Scholar
Zou, C. et al. Identification of immune-related risk signatures for the prognostic prediction in oral squamous cell carcinoma. J. Immunol. Res. 2021, 6203759 (2021).
Article PubMed Central PubMed Google Scholar
Macenko, M., Niethammer, M., Marron, J.S., Borland, D., Woosley, J.T., Xiaojun, G., et al. A method for normalizing histology slides for quantitative analysis. In 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2009 (IEEE, accessed 4 Apr 2023]. P. 11071110. http://ieeexplore.ieee.org/document/5193250/
Vahadane, A. et al. Structure-preserving color normalization and sparse stain separation for histological images. IEEE Trans. Med. Imaging 35, 19621971 (2016).
Article PubMed Google Scholar
Salvi, M., Acharya, U. R., Molinari, F. & Meiburger, K. M. The impact of pre- and post-image processing techniques on deep learning frameworks: A comprehensive review for digital pathology image analysis. Comput. Biol. Med. 128, 104129 (2021).
Article PubMed Google Scholar
Carpenter, A. E. et al. Cell Profiler: Image analysis software for identifying and quantifying cell phenotypes. Genome Biol. 7, R100 (2006).
Article PubMed Central PubMed Google Scholar
Hughey, J. J. & Butte, A. J. Robust meta-analysis of gene expression using the elastic net. Nucleic Acids Res. 43, e79 (2015).
Article PubMed Central PubMed Google Scholar
Tschodu, D. et al. Re-evaluation of publicly available gene-expression databases using machine-learning yields a maximum prognostic power in breast cancer. Sci. Rep. 13, 16402 (2023).
Article CAS PubMed Central ADS PubMed Google Scholar
Kanehisa, M. & Goto, S. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28, 2730 (2000).
Article CAS PubMed Central PubMed Google Scholar
Kanehisa, M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 28, 19471951 (2019).
Article CAS PubMed Central PubMed Google Scholar
Kanehisa, M., Furumichi, M., Sato, Y., Kawashima, M. & Ishiguro-Watanabe, M. KEGG for taxonomy-based analysis of pathways and genomes. Nucleic Acids Res. 51, D587D592 (2023).
Article CAS PubMed Google Scholar
Ye, H. et al. Metabolism-related bioinformatics analysis reveals that HPRT1 facilitates the progression of oral squamous cell carcinoma in vitro. J. Oncol. 2022, 116 (2022).
Google Scholar
Ferreira, A.-K. et al. Survival and prognostic factors in patients with oral squamous cell carcinoma. Med. Oral. Patol. Oral. Cir. Bucal. 26, e387e392 (2021).
Article PubMed Google Scholar
Asio, J., Kamulegeya, A. & Banura, C. Survival and associated factors among patients with oral squamous cell carcinoma (OSCC) in Mulago hospital, Kampala, Uganda. Cancers Head Neck. 3, 9 (2018).
Article PubMed Central PubMed Google Scholar
Girod, A., Mosseri, V., Jouffroy, T., Point, D. & Rodriguez, J. Women and squamous cell carcinomas of the oral cavity and oropharynx: Is there something new?. J. Oral Maxillof. Surg. 67, 19141920 (2009).
Article Google Scholar
Wong, K., Rostomily, R. & Wong, S. Prognostic gene discovery in glioblastoma patients using deep learning. Cancers 11, 53 (2019).
Article CAS PubMed Central PubMed Google Scholar
Hsich, E., Gorodeski, E. Z., Blackstone, E. H., Ishwaran, H. & Lauer, M. S. Identifying important risk factors for survival in patient with systolic heart failure using random survival forests. Circ. Cardiovasc. Qual. Outcomes 4, 3945 (2011).
Article PubMed Google Scholar
Ishwaran, H., Kogalur, U. B., Gorodeski, E. Z., Minn, A. J. & Lauer, M. S. High-dimensional variable selection for survival data. J. Am. Stat. Assoc. 105, 20517 (2010).
Article MathSciNet CAS Google Scholar
Ishwaran, H., Kogalur, U. B., Chen, X. & Minn, A. J. Random survival forests for high-dimensional data. Stat. Anal. Data Min. ASA Data Sci. J. 2011(4), 11532 (2011).
Article MathSciNet Google Scholar
Katzman, J. L. et al. Deepsurv: personalized treatment recommender system using a cox proportional hazards deep neural network. BMC Med. Res. Methol. 18, 187202 (2018).
Google Scholar
Sargent, D. J. Comparison of artificial neural networks with other statistical approaches. Cancer 91, 16361642 (2001).
Article CAS PubMed Google Scholar
Xiang, A., Lapuerta, P., Ryutov, A., Buckley, J. & Azen, S. Comparison of the performance of neural network methods and Cox regression for censored survival data. Comput. Stat. Data Anal. 34, 24357 (2000).
Article Google Scholar
Nie, Z., Zhao, P., Shang, Y. & Sun, B. Nomograms to predict the prognosis in locally advanced oral squamous cell carcinoma after curative resection. BMC Cancer 21, 372 (2021).
Article PubMed Central PubMed Google Scholar
Nojavanasghari, B., Gopinath, D., Koushik, J., Baltruaitis, T., & Morency, L. P. Deep multimodal fusion for persuasiveness prediction. In Proceedings of the 18th ACM International Conference on Multimodal Interaction. 284288 (2016).
Kampman, O., Barezi, E. J., Bertero, D., & Fung, P. Investigating audio, video, and text fusion methods for end-to-end automatic personality prediction. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics vol. 2.606611 (2018).
Wang, Z., Li, R., Wang, M. & Li, A. Gpdbn: Deep bilinear network integrating both genomic data and pathological images for breast cancer prognosis prediction. Bioinformatics 27, 29632970 (2021).
Article Google Scholar
Subramanian, V., Syeda-Mahmood, T., & Do, M. N. Multimodal fusion using sparse cca for breast cancer survival prediction. In Proceedings of IEEE 18th International Symposium on Biomedical Imaging (ISBI).14291432 (2021).
Mai, S., Hu, H., & Xing, S. Modality to modality translation: An adversarial representation learning and graph fusion network for multimodal fusion. In Proceedings of the AAAI Conference on Artificial Intelligence 164172 (2020).
Mobadersany, P. et al. Predicting cancer outcomes from histology and genomics. Predicting cancer outcomes from histology and genomics using convolutional networks. Proc. Natl. Acad. Sci. 115, 29702979 (2018).
Article ADS Google Scholar
Wang, C. et al. A cancer survival prediction method based on graph convolutional network. IEEE Trans. Nanobiosci. 19, 117126 (2020).
Article Google Scholar
Zadeh, A., Chen, M., Poria, S., Cambria, E., & Morency, L. P Tensor fusion network for multimodal sentiment analysis. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 11031114 (2017).
Chen, R. J. et al. Pathomic fusion: An integrated framework for fusing histopathology and genomic features for cancer diagnosis and prognosis. IEEE Trans. Med. Imaging 41, 757770 (2022).
Article PubMed Central PubMed Google Scholar
Kim, J. H., On, K. W., Lim, W., Kim, J., Ha, J. W., & Zhang, B. T. Hadamard product for low-rank bilinear pooling. In Proceedings of International Conference on Learning Representations, 114 (2017)
Liu, Z., Shen, Y., Lakshminarasimhan, V. B., Liang, P. P., Zadeh, A., & Morency, L. P. Efficient low-rank multimodal fusion with modality-specific factors. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics. 22472256 (2021)
Li, R., Wu, X., Li, A. & Wang, M. Hfbsurv: Hierarchical multimodal fusion with factorized bilinear models for cancer survival prediction. Bioinformatics 38, 25872594 (2022).
Article CAS PubMed Central PubMed Google Scholar
Original post:
Multimodal artificial intelligence-based pathogenomics improves survival prediction in oral squamous cell carcinoma ... - Nature.com
- Machine learning and generative AI: What are they good for in 2025? - MIT Sloan - June 4th, 2025 [June 4th, 2025]
- Researchers use machine learning to improve gene therapy - Stanford Report - June 4th, 2025 [June 4th, 2025]
- Machine learning for workpiece mass prediction using real and synthetic acoustic data - Nature - June 4th, 2025 [June 4th, 2025]
- Analyzing the Effect of Linguistic Similarity on Cross-Lingual Transfer: Tasks and Input Representations Matter - Apple Machine Learning Research - June 4th, 2025 [June 4th, 2025]
- Machine learning models for predicting severe acute kidney injury in patients with sepsis-induced myocardial injury - Nature - June 4th, 2025 [June 4th, 2025]
- A machine learning approach to carbon emissions prediction of the top eleven emitters by 2030 and their prospects for meeting Paris agreement targets... - June 4th, 2025 [June 4th, 2025]
- Augmentation of wastewater-based epidemiology with machine learning to support global health surveillance - Nature - June 4th, 2025 [June 4th, 2025]
- Analysis of a nonsteroidal anti inflammatory drug solubility in green solvent via developing robust models based on machine learning technique -... - June 4th, 2025 [June 4th, 2025]
- Your DNA Is a Machine Learning Model: Its Already Out There - Towards Data Science - June 4th, 2025 [June 4th, 2025]
- Development and validation of a risk prediction model for kinesiophobia in postoperative lung cancer patients: an interpretable machine learning... - June 4th, 2025 [June 4th, 2025]
- Predicting long-term patency of radiocephalic arteriovenous fistulas with machine learning and the PREDICT-AVF web app - Nature - June 4th, 2025 [June 4th, 2025]
- How Machine Learning and Cascade Learning Open Doors of Advanced Automation - Supply & Demand Chain Executive - June 4th, 2025 [June 4th, 2025]
- New Hydrogenation Reaction Mechanism for Superhydride Revealed by Machine Learning - Asia Research News | - June 4th, 2025 [June 4th, 2025]
- AI experiences rapid adoption, but with mixed outcomes Highlights from VotE: AI & Machine Learning - S&P Global - June 4th, 2025 [June 4th, 2025]
- IIPE introduces online M.Tech in Data Science and Machine Learning for working professionals - India Today - June 4th, 2025 [June 4th, 2025]
- Introducing Windows ML: The future of machine learning development on Windows - Windows Blog - May 19th, 2025 [May 19th, 2025]
- Settlement strategies and their driving mechanisms of Neolithic settlements using machine learning approaches: a case study in Zhejiang Province -... - May 19th, 2025 [May 19th, 2025]
- MyWear revolutionizes real-time health monitoring with comparative analysis of machine learning - Nature - May 19th, 2025 [May 19th, 2025]
- Leveraging stacking machine learning models and optimization for improved cyberattack detection - Nature - May 19th, 2025 [May 19th, 2025]
- Predicting land suitability for wheat and barley crops using machine learning techniques - Nature - May 10th, 2025 [May 10th, 2025]
- AI and Machine Learning - Ribeiro Preto adopts Optibus to optimise public bus system - Smart Cities World - May 10th, 2025 [May 10th, 2025]
- Childrens Hospital Los Angeles Leads Development of First Machine Learning Tool to Predict Risk of Cisplatin-Induced Hearing Loss - Business Wire - May 10th, 2025 [May 10th, 2025]
- Google is using machine learning to help Android users avoid unwanted and dangerous notifications - BetaNews - May 10th, 2025 [May 10th, 2025]
- London School of Emerging Technology (LSET) Concludes International Workshop on Emerging AI & Machine Learning Innovation - Barchart.com - May 10th, 2025 [May 10th, 2025]
- Thermal performance, entropy generation, and machine learning insights of AlO-TiO hybrid nanofluids in turbulent flow - Nature - May 10th, 2025 [May 10th, 2025]
- Predicting the efficacy of bevacizumab on peritumoral edema based on imaging features and machine learning - Nature - May 10th, 2025 [May 10th, 2025]
- How AI and machine learning are supercharging video conferencing tools - European CEO - May 10th, 2025 [May 10th, 2025]
- The need for a risk-based approach to AI and machine learning in healthcare - Health Tech World - May 10th, 2025 [May 10th, 2025]
- Integrated bioinformatics, machine learning, and molecular docking reveal crosstalk genes and potential drugs between periodontitis and systemic lupus... - May 10th, 2025 [May 10th, 2025]
- Adversarial Machine Learning in Detecting Inauthentic Behavior on Social Platforms - AiThority - May 10th, 2025 [May 10th, 2025]
- Exploring crop health and its associations with fungal soil microbiome composition using machine learning applied to remote sensing data - Nature - May 10th, 2025 [May 10th, 2025]
- Trust-based model and machine learning improve forest fire detection system - International Fire & Safety Journal - May 10th, 2025 [May 10th, 2025]
- A machine learning engineer shares the rsums that landed her jobs at Meta and X and what she'd change if she applied again - Business Insider Africa - May 5th, 2025 [May 5th, 2025]
- Recentive Analytics v. Fox: The Federal Circuit Provides Analysis on the Patent Eligibility of Machine Learning Claims - Mintz - May 5th, 2025 [May 5th, 2025]
- A machine learning engineer shares the rsums that landed her jobs at Meta and X and what she'd change if she applied again - Business Insider - May 5th, 2025 [May 5th, 2025]
- Enhancing urban resilience through machine learning-supported flood risk assessment: integrating flood susceptibility with building function... - May 5th, 2025 [May 5th, 2025]
- MicroAlgo Inc. Develops Classifier Auto-Optimization Technology Based on Variational Quantum Algorithms, Accelerating the Advancement of Quantum... - May 5th, 2025 [May 5th, 2025]
- Enhanced metal ion adsorption using ZnO-MXene nanocomposites with machine learning-based performance prediction - Nature - May 5th, 2025 [May 5th, 2025]
- Integrating SHAP analysis with machine learning to predict postpartum hemorrhage in vaginal births - BMC Pregnancy and Childbirth - May 5th, 2025 [May 5th, 2025]
- Machine learning provide new insights into how the brain responds to heroin use - News-Medical - May 2nd, 2025 [May 2nd, 2025]
- Machine Learning and AI in Basic HIV Research: From Big Data Analysis to Large Language Models - UNC Gillings School of Global Public Health - May 2nd, 2025 [May 2nd, 2025]
- Machine learning brings new insights to cells role in addiction, relapse - University of Cincinnati - May 2nd, 2025 [May 2nd, 2025]
- UH/UC Researchers Use Machine Learning to Map Brain Changes from Heroin Addiction - University of Houston - May 2nd, 2025 [May 2nd, 2025]
- Machine Learning Algorithm Predicts Shiba Inu Price In May You Should See This - The Crypto Update - May 2nd, 2025 [May 2nd, 2025]
- Seerist partners with SOCOM to enhance AI and machine learning for special operations - Defence Industry Europe - May 2nd, 2025 [May 2nd, 2025]
- How machine learning can spark many discoveries in science and medicine - The Indian Express - April 30th, 2025 [April 30th, 2025]
- Machine learning frameworks to accurately estimate the adsorption of organic materials onto resin and biochar - Nature - April 30th, 2025 [April 30th, 2025]
- Gene Therapy Research Roundup: Gene Circuits and Controlling Capsids With Machine Learning - themedicinemaker.com - April 30th, 2025 [April 30th, 2025]
- Seerist and SOCOM Enter Five-Year CRADA to Advance AI and Machine Learning for Operations - PRWeb - April 30th, 2025 [April 30th, 2025]
- Machine learning models for estimating the overall oil recovery of waterflooding operations in heterogenous reservoirs - Nature - April 30th, 2025 [April 30th, 2025]
- Machine learning-based quantification and separation of emissions and meteorological effects on PM - Nature - April 30th, 2025 [April 30th, 2025]
- Protein interactions, network pharmacology, and machine learning work together to predict genes linked to mitochondrial dysfunction in hypertrophic... - April 30th, 2025 [April 30th, 2025]
- AQR Bets on Machine Learning as Asness Becomes AI Believer - Bloomberg.com - April 30th, 2025 [April 30th, 2025]
- Darktrace enhances Cyber AI Analyst with advanced machine learning for improved threat investigations - Industrial Cyber - April 21st, 2025 [April 21st, 2025]
- Infrared spectroscopy with machine learning detects early wood coating deterioration - Phys.org - April 21st, 2025 [April 21st, 2025]
- A simulation-driven computational framework for adaptive energy-efficient optimization in machine learning-based intrusion detection systems - Nature - April 21st, 2025 [April 21st, 2025]
- Machine learning model to predict the fitness of AAV capsids for gene therapy - EurekAlert! - April 21st, 2025 [April 21st, 2025]
- An integrated approach of feature selection and machine learning for early detection of breast cancer - Nature - April 21st, 2025 [April 21st, 2025]
- Predicting cerebral infarction and transient ischemic attack in healthy individuals and those with dysmetabolism: a machine learning approach combined... - April 21st, 2025 [April 21st, 2025]
- Autolomous CEO Discusses AI and Machine Learning Applications in Pharmaceutical Development and Manufacturing with Pharmaceutical Technology -... - April 21st, 2025 [April 21st, 2025]
- Machine Learning Interpretation of Optical Spectroscopy Using Peak-Sensitive Logistic Regression - ACS Publications - April 21st, 2025 [April 21st, 2025]
- Estimated glucose disposal rate outperforms other insulin resistance surrogates in predicting incident cardiovascular diseases in... - April 21st, 2025 [April 21st, 2025]
- Machine learning-based differentiation of schizophrenia and bipolar disorder using multiscale fuzzy entropy and relative power from resting-state EEG... - April 12th, 2025 [April 12th, 2025]
- Increasing load factor in logistics and evaluating shipment performance with machine learning methods: A case from the automotive industry - Nature - April 12th, 2025 [April 12th, 2025]
- Machine learning-based prediction of the thermal conductivity of filling material incorporating steelmaking slag in a ground heat exchanger system -... - April 12th, 2025 [April 12th, 2025]
- Do LLMs Know Internally When They Follow Instructions? - Apple Machine Learning Research - April 12th, 2025 [April 12th, 2025]
- Leveraging machine learning in precision medicine to unveil organochlorine pesticides as predictive biomarkers for thyroid dysfunction - Nature - April 12th, 2025 [April 12th, 2025]
- Analysis and validation of hub genes for atherosclerosis and AIDS and immune infiltration characteristics based on bioinformatics and machine learning... - April 12th, 2025 [April 12th, 2025]
- AI and Machine Learning - Bentley and Google partner to improve asset analytics - Smart Cities World - April 12th, 2025 [April 12th, 2025]
- Where to find the next Earth: Machine learning accelerates the search for habitable planets - Phys.org - April 10th, 2025 [April 10th, 2025]
- Concurrent spin squeezing and field tracking with machine learning - Nature - April 10th, 2025 [April 10th, 2025]
- This AI Paper Introduces a Machine Learning Framework to Estimate the Inference Budget for Self-Consistency and GenRMs (Generative Reward Models) -... - April 10th, 2025 [April 10th, 2025]
- UCI researchers study use of machine learning to improve stroke diagnosis, access to timely treatment - UCI Health - April 10th, 2025 [April 10th, 2025]
- Assessing dengue forecasting methods: a comparative study of statistical models and machine learning techniques in Rio de Janeiro, Brazil - Tropical... - April 10th, 2025 [April 10th, 2025]
- Machine learning integration of multimodal data identifies key features of circulating NT-proBNP in people without cardiovascular diseases - Nature - April 10th, 2025 [April 10th, 2025]
- How AI, Data Science, And Machine Learning Are Shaping The Future - Forbes - April 10th, 2025 [April 10th, 2025]
- Development and validation of interpretable machine learning models to predict distant metastasis and prognosis of muscle-invasive bladder cancer... - April 10th, 2025 [April 10th, 2025]
- From fax machines to machine learning: The fight for efficiency - HME News - April 10th, 2025 [April 10th, 2025]
- Carbon market and emission reduction: evidence from evolutionary game and machine learning - Nature - April 10th, 2025 [April 10th, 2025]
- Infleqtion Unveils Contextual Machine Learning (CML) at GTC 2025, Powering AI Breakthroughs with NVIDIA CUDA-Q and Quantum-Inspired Algorithms - Yahoo... - March 22nd, 2025 [March 22nd, 2025]