Shall You Get an Invasive Examination? An AI-Driven Risk Stratification Model for Individuals with Suboptimal Health Status
Published Online:15 Jun 2026https://doi.org/10.1287/serv.2025.0067
References
- (2023) Machine learning-based colorectal cancer prediction using global dietary data. BMC Cancer 23(1):144.Crossref, Google Scholar
- (2023) Artificial intelligence–based chatbots for promoting health behavioral changes: Systematic review. J. Medical Internet Res. 25:e40789.Crossref, Google Scholar
- (2020) Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine. Database 2020(2020):baaa010.Google Scholar
- (2023) A systematic review of trustworthy and explainable artificial intelligence in healthcare: Assessment of quality, bias risk, and data fusion. Inform. Fusion 96:156–191.Crossref, Google Scholar
- (2019) A fast machine learning model for ECG-based heartbeat classification and arrhythmia detection. Frontiers Phys. 7:103.Crossref, Google Scholar
- (2023) A systematic literature review of artificial intelligence in the healthcare sector: Benefits, challenges, methodologies, and functionalities. J. Innovation Knowledge 8(1):100333.Crossref, Google Scholar
- (2023) Revolutionizing healthcare: The role of artificial intelligence in clinical practice. BMC Medical Ed. 23(1):689.Crossref, Google Scholar
- (2020) A novel and reliable framework of patient deterioration prediction in intensive care unit based on long short-term memory-recurrent neural network. IEEE Access 9:3894–3918.Crossref, Google Scholar
- Consortium PQ (2020) Explainability for artificial intelligence in healthcare: A multidisciplinary perspective. BMC Medical Inform. Decision Making 20:1–9.Crossref, Google Scholar
- (2023) Cost-effectiveness of artificial intelligence-aided colonoscopy for adenoma detection in colon cancer screening. J. Canadian Assoc. Gastroenterology 6(3):97–105.Crossref, Google Scholar
- (2020) Machine learning in oncology: Methods, applications, and challenges. JCO Clinical Cancer Inform. 4, 885–894.Google Scholar
- (2023) Survey of explainable AI techniques in healthcare. Sensors 23(2):634.Crossref, Google Scholar
- (2023) Proactive steps to population health: Starting early, starting right. Ann. Acad. Medicine Singapore 52(6):278–279.Crossref, Google Scholar
- (2024) Artificial intelligence and value co-creation: A review, conceptual framework and directions for future research. J. Service Theory Practice 34(1):7–32.Crossref, Google Scholar
- (2002) SMOTE: Synthetic minority over-sampling technique. J. Artificial Intelligence Res. 16:321–357.Crossref, Google Scholar
- (2016) Retain: An interpretable predictive model for healthcare using reverse time attention mechanism. Adv. Neural Inform. Processing Systems 29.Google Scholar
- (2018) Classification and mutation prediction from non-small cell lung cancer histopathology images using deep learning. Nature Medicine 24(10):1559–1567.Crossref, Google Scholar
- (2019) The potential for artificial intelligence in healthcare. Future Healthcare J. 6(2):94–98.Crossref, Google Scholar
- (2019) A guide to deep learning in healthcare. Nature Medicine 25(1):24–29.Crossref, Google Scholar
- (2015) Decision curve analysis. JAMA 313(4):409–410.Crossref, Google Scholar
- He RY, Chiang JN (2024) TFT-multi: Simultaneous forecasting of vital sign trajectories in the ICU. Preprint, submitted September 23, https://arxiv.org/abs/2409.15586.Google Scholar
- (1997) Long short-term memory. Neural Comput. 9(8):1735–1780.Crossref, Google Scholar
- (2018) Artificial intelligence in radiology. Nature Rev. Cancer 18(8):500–510.Crossref, Google Scholar
- (2023) Optimization of colonoscopy quality: Comprehensive review of the literature and future perspectives. Digestive Endoscopy 35(7):822–834.Crossref, Google Scholar
- (2018) Artificial intelligence in service. J. Service Res. 21(2):155–172.Crossref, Google Scholar
- (2023) Explainable artificial intelligence (XAI): Concepts and challenges in healthcare. AI 4(3):652–666.Crossref, Google Scholar
- (2017) Artificial intelligence in healthcare: Past, present and future. Stroke Vascular Neurology 2(4).Crossref, Google Scholar
- (2021) Characteristics of online health care services from China’s largest online medical platform: Cross-sectional survey study. J. Medical Internet Res. 23(4):e25817.Crossref, Google Scholar
- (2020) Multimodal brain tumor classification using deep learning and robust feature selection: A machine learning application for radiologists. Diagnostics 10(8):565.Crossref, Google Scholar
- (2023) Data-centric AI solutions and emerging technologies in the healthcare ecosystem. CRC Press 10(978100335618):9.Google Scholar
- (2025) Artificial intelligence in healthcare and its implications for patient centered care. Discovery Public Health 22(1):524.Crossref, Google Scholar
- (2023) Artificial intelligence-supported screen reading versus standard double reading in the Mammography Screening with Artificial Intelligence trial (MASAI): A clinical safety analysis of a randomised, controlled, non-inferiority, single-blinded, screening accuracy study. Lancet Oncology 24(8):936–944.Crossref, Google Scholar
- (2019) Deep learning in drug discovery: Opportunities, challenges and future prospects. Drug Discovery Today 24(10):2017–2032.Crossref, Google Scholar
- (2021) Application of artificial intelligence-based technologies in the healthcare industry: Opportunities and challenges. Internat. J. Environment. Res. Public Health 18(1):271.Crossref, Google Scholar
- (2021) How does artificial intelligence enable and enhance value co-creation in industrial markets? An exploratory case study in the healthcare ecosystem. J. Bus. Res. 129:849–859.Crossref, Google Scholar
- (2018) Data-driven understanding of smart service systems through text mining. Service Sci. 10(2):154–180.Link, Google Scholar
- (2021) Temporal fusion transformers for interpretable multi-horizon time series forecasting. Internat. J. Forecasting 37(4):1748–1764.Crossref, Google Scholar
- (2020) Enhanced Youden’s index with net benefit: A feasible approach for optimal‐threshold determination in shared decision making. J. Evaluation Clinical Practice 26(2):551–558.Crossref, Google Scholar
- (2015) Service innovation. MIS Quart. 39(1):155–176.Crossref, Google Scholar
- (2024) Risk factors, health status, and risk groups in suboptimal health condition. All Around Suboptimal Health: Advanced Approaches by Predictive, Preventive and Personalised Medicine for Healthy Populations (Springer Nature, Cham, Switzerland), 61–72.Crossref, Google Scholar
- (2023) Artificial intelligence in drug discovery and development. Drug Discovery and Evaluation: Safety and Pharmacokinetic Assays, 1–38.Crossref, Google Scholar
- (2022) Mapping definitions of co‐production and co‐design in health and social care: A systematic scoping review providing lessons for the future. Health Expectations 25(3):902–913.Crossref, Google Scholar
- (2006) Demographics and tumor characteristics of colorectal cancers in the United States, 1998–2001. Cancer 107(S5):1112–1120.Crossref, Google Scholar
- (2020) International evaluation of an AI system for breast cancer screening. Nature 577(7788):89–94.Crossref, Google Scholar
- (2004) Influence of demographics on colorectal cancer. Am. Surgery 70(3):259–264.Crossref, Google Scholar
- (2021) Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015–20): A comparative analysis. Lancet Digital Health 3(3):e195–e203.Crossref, Google Scholar
- (2022) Receiver operating characteristic curve: Overview and practical use for clinicians. Korean J. Anesthesiology 75(1):25–36.Crossref, Google Scholar
- (2016) Predicting the future—Big data, machine learning, and clinical medicine. New England J. Medicine 375(13):1216–1219.Crossref, Google Scholar
- (2024) The rise of non-communicable diseases: A global health review of challenges and prevention strategies. Internat. Medical Sci. Res. J. 4(1):74–88.Crossref, Google Scholar
- (2015) Service research priorities in a rapidly changing context. J. Service Res. 18(2):127–159.Crossref, Google Scholar
- (2023) The burden of nonalcoholic fatty liver disease (NAFLD) is rapidly growing in every region of the world from 1990 to 2019. Hepatology Comm. 7(10):e0251.Crossref, Google Scholar
- (2025) Application of artificial intelligence in the health management of chronic disease: Bibliometric analysis. Frontiers Medicine (Lausanne) 11:1506641.Crossref, Google Scholar
- (2019) Privacy in the age of medical big data. Nature Medicine 25(1):37–43.Crossref, Google Scholar
- (2024) Machine learning empowering drug discovery: Applications, opportunities and challenges. Molecules 29(4):903.Crossref, Google Scholar
- (2021) Deep neural networks can predict new-onset atrial fibrillation from the 12-lead ECG and help identify those at risk of atrial fibrillation–related stroke. Circulation 143(13):1287–1298.Crossref, Google Scholar
- (2024) Enhancing heart disease prediction using a self-attention-based transformer model. Sci. Rep. 14(1):514.Crossref, Google Scholar
- (2022) AI in health and medicine. Nature Medicine 28(1):31–38.Crossref, Google Scholar
- (2018) Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists. PLoS Medicine 15(11):e1002686.Crossref, Google Scholar
- (2019) Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Nature Machine Intelligence 1(5):206–215.Crossref, Google Scholar
- (2024) A review of explainable artificial intelligence in healthcare. Comput. Electrical Engrg. 118:109370.Crossref, Google Scholar
- (2024) Systemic impacts of metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH) on heart, muscle, and kidney related diseases. Frontiers Cell Development Biology 12:1433857.Crossref, Google Scholar
- (2020) Rethinking drug design in the artificial intelligence era. Nature Rev. Drug Discovery 19(5):353–364.Crossref, Google Scholar
- (2021) The role of artificial intelligence in healthcare: A structured literature review. BMC Medical Inform. Decision Making 21:1–23.Crossref, Google Scholar
- (2021) ACG clinical guidelines: Colorectal cancer screening 2021. Amer. J. Gastroenterology 116(3):458–479.Crossref, Google Scholar
- (2020) Deep learning for prediction of colorectal cancer outcome: A discovery and validation study. Lancet 395(10221):350–360.Crossref, Google Scholar
- (2026) Leading cancer deaths in people younger than 50 years. JAMA.Crossref, Google Scholar
- (2023) Digital transformation in healthcare: Technology acceptance and its applications. Internat. J. Environment. Res. Public Health 20(4):3407.Crossref, Google Scholar
- (2021) Artificial intelligence in healthcare: Opportunities and risk for future. Gaceta Sanitaria 35:S67–S70.Crossref, Google Scholar
- (2021) Artificial intelligence-assisted colonoscopy: A review of current state of practice and research. World J. Gastroenterology 27(47):8103.Crossref, Google Scholar
- (2014) Feature selection for classification: A review. Data Classification: Algorithms Applications (CRC Press, Chapman & Hall), 37–64.Google Scholar
- (2024) Enhancing disease prediction with a hybrid CNN-LSTM framework in EHRS. J. Theory Practice Engrg. Sci. 4(02):8–14.Crossref, Google Scholar
- (2019) High-performance medicine: The convergence of human and artificial intelligence. Nature Medicine 25(1):44–56.Crossref, Google Scholar
- (2019) Chatbots and conversational agents in mental health: A review of the psychiatric landscape. Canadian J. Psychiatry 64(7):456–464.Crossref, Google Scholar
- (2019) Applications of machine learning in drug discovery and development. Nature Rev. Drug Discovery 18(6):463–477.Crossref, Google Scholar
- (2008) Service-dominant logic: Continuing the evolution. J. Acad. Marketing Sci. 36:1–10.Crossref, Google Scholar
- (2006) Decision curve analysis: A novel method for evaluating prediction models. Medical Decision Making 26(6):565–574.Crossref, Google Scholar
- (2019) Suboptimal health status and cardiovascular deficits. Flammer Syndrome: From Phenotype to Associated Pathologies, Prediction, Prevention and Personalisation (Springer, Cham, Switzerland), 287–315.Crossref, Google Scholar
- (2012) Suboptimal health: A new health dimension for translational medicine. Clinical Translation Medicine 1:1–6.Crossref, Google Scholar
- (2021) Chatbot for health care and oncology applications using artificial intelligence and machine learning: Systematic review. JMIR Cancer 7(4):e27850.Crossref, Google Scholar
- (2021) Artificial intelligence–enabled electrocardiograms for identification of patients with low ejection fraction: A pragmatic, randomized clinical trial. Nature Medicine 27(5):815–819.Crossref, Google Scholar
- (1950) Index for rating diagnostic tests. Cancer 3(1):32–35.Crossref, Google Scholar
- (2024) Epidemiology of metabolic dysfunction-associated steatotic liver disease. Clinical Molecular Hepatology 31(suppl):S32.Crossref, Google Scholar

