4.6 Article

Explainable ensemble learning model improves identification of candidates for oral cancer screening

Related references

Note: Only part of the references are listed.
Article Computer Science, Artificial Intelligence

Relation between prognostics predictor evaluation metrics andlocal interpretability SHAP values

Marcia L. Baptista et al.

Summary: Maintenance decisions in domains like aeronautics rely heavily on predicting component and system failures using data-driven techniques. However, the lack of interpretability has been a challenge for these techniques. This study examines the correlation between features used in data-driven prognostic approaches and established metrics, using the SHAP model from explainable artificial intelligence. The results show that SHAP values closely align with the prognostic metrics, highlighting the significance of model complexity in explainability.

ARTIFICIAL INTELLIGENCE (2022)

Article Biochemical Research Methods

Ten simple rules for researchers who want to develop web apps

Sheila M. Saia et al.

PLOS COMPUTATIONAL BIOLOGY (2022)

Review Health Care Sciences & Services

Guidelines and quality criteria for artificial intelligence-based prediction models in healthcare: a scoping review

Anne A. H. de Hond et al.

Summary: This article collects guidance on the development, evaluation, and implementation of AI-based prediction models in healthcare, finding that there is more detailed guidance for early stages such as data preparation, AIPM development, and AIPM validation, while later stages such as software development, impact assessment, and implementation have received less attention.

NPJ DIGITAL MEDICINE (2022)

Article Dentistry, Oral Surgery & Medicine

Performance of a simplified scoring system for risk stratification in oral cancer and oral potentially malignant disorders screening

John Adeoye et al.

Summary: This study aimed to optimize a simplified risk scoring system for risk stratification in organized oral cancer and oral potentially malignant disorders screening. The researchers generated a 12-variable simplified risk scoring system through oral examination and information collection from participants in Hong Kong, and validated it. The results showed that this scoring system could satisfactorily stratify the risk of oral cancer and oral potentially malignant disorders.

JOURNAL OF ORAL PATHOLOGY & MEDICINE (2022)

Article Oncology

Risk-Based Selection of Individuals for Oral Cancer Screening

Li C. Cheung et al.

Summary: The study demonstrated the potential of risk-based oral cancer screening to enhance screening efficiency. Oral cancer screening significantly reduced oral cancer mortality rates, especially in high-risk individuals.

JOURNAL OF CLINICAL ONCOLOGY (2021)

Review Computer Science, Information Systems

Prediction models applying machine learning to oral cavity cancer outcomes: A systematic review

John Adeoye et al.

Summary: Machine learning models in oral cavity cancer management have shown satisfactory to excellent accuracy in predicting malignant transformation, nodal metastasis, and prognosis. However, the training approach of these classifiers may not be streamlined enough for current clinical application. Models incorporating molecular markers in training data demonstrated better accuracy estimates.

INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS (2021)

Article Oncology

Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

Hyuna Sung et al.

Summary: The global cancer burden in 2020 saw an estimated 19.3 million new cancer cases and almost 10.0 million cancer deaths. Female breast cancer surpassed lung cancer as the most commonly diagnosed cancer, while lung cancer remained the leading cause of cancer death. These trends are expected to rise in 2040, with transitioning countries experiencing a larger increase compared to transitioned countries due to demographic changes and risk factors associated with globalization and a growing economy. Efforts to improve cancer prevention measures and provision of cancer care in transitioning countries will be crucial for global cancer control.

CA-A CANCER JOURNAL FOR CLINICIANS (2021)

Article Medicine, General & Internal

Serum levels and positive rates of tumor biomarkers in oral precancer patients

Yu-Hsueh Wu et al.

Summary: This study found significantly higher serum levels and positive rates of CEA, SCC-Ag, and ferritin in oral precancer patients compared to healthy control subjects, suggesting potential diagnostic value of these tumor markers for screening and diagnosis of oral precancer.

JOURNAL OF THE FORMOSAN MEDICAL ASSOCIATION (2021)

Review Computer Science, Artificial Intelligence

Machine learning in oral squamous cell carcinoma: Current status, clinical concerns and prospects for future-A systematic review

Rasheed Omobolaji Alabi et al.

Summary: Machine learning has shown promising potential in revolutionizing the diagnosis and prognosis of oral squamous cell carcinoma, but faces limitations and concerns in clinical implementation.

ARTIFICIAL INTELLIGENCE IN MEDICINE (2021)

Article Dentistry, Oral Surgery & Medicine

Prognostic value of non-smoking, non-alcohol drinking status in oral cavity cancer

John Adeoye et al.

Summary: Treatment response and disease-specific prognosis are comparable between non-smoking and non-alcohol-drinking (NSND) patients and smoking and alcohol-drinking (SD) patients with oral cavity cancer. However, NSND patients have better overall survival.

CLINICAL ORAL INVESTIGATIONS (2021)

Article Oncology

Deep Learning Predicts the Malignant-Transformation-Free Survival of Oral Potentially Malignant Disorders

John Adeoye et al.

Summary: Machine learning models were used to predict malignancy from oral white lesions with satisfactory performance and stability. DeepSurv and RSF were the top-performing models in terms of discrimination and calibration in internal validation. DeepSurv was more stable than RSF in cross-validation, with external validation confirming their utility for discrimination and individual survival estimates.

CANCERS (2021)

Review Health Care Sciences & Services

Clinical impact and quality of randomized controlled trials involving interventions evaluating artificial intelligence prediction tools: a systematic review

Qian Zhou et al.

Summary: The study found that the evidence of the impact of TS, ML, and DL tools in clinical practice was limited, with DL applications not yet fully spread in medicine. In the future, DL may integrate more complex clinical problems than ML and TS tools. Rigorous studies are required before the clinical application of these tools.

NPJ DIGITAL MEDICINE (2021)

Review Otorhinolaryngology

Fact or fiction?: Oral cavity cancer in nonsmoking, nonalcohol drinking patients as a distinct entity-Scoping review

John Adeoye et al.

Summary: Oral cavity cancer is often linked with lifestyle factors like smoking and drinking, but there are also cases unrelated to these habits, with patients typically being elderly females with tumors on the tongue and gingivobuccal mucosa, diagnosed early with high levels of PD-L1 expression. Treatment response and prognosis are similar between these patients and those who smoke or drink.

HEAD AND NECK-JOURNAL FOR THE SCIENCES AND SPECIALTIES OF THE HEAD AND NECK (2021)

Review Dentistry, Oral Surgery & Medicine

Oral Cancer Screening: Past, Present, and Future

S. Warnakulasuriya et al.

Summary: Oral cancer is a significant public health issue, affecting young individuals with poor public awareness. Early detection through visual inspection of premalignant lesions before oral cancer develops can reduce mortality. Screening for high-risk groups is cost-effective, but population-based screening lacks sufficient evidence.

JOURNAL OF DENTAL RESEARCH (2021)

Review Medicine, General & Internal

Predicting the risk of cancer in adults using supervised machine learning: a scoping review

Asma Abdullah Alfayez et al.

Summary: This study aims to identify and compare existing supervised machine learning approaches for predicting cancer in asymptomatic adults, and to identify potential research gaps. Results show that current machine learning models for predicting future cancer risk still have shortcomings in transparency and clinical utility.

BMJ OPEN (2021)

Review Oncology

Overview of Oral Potentially Malignant Disorders: From Risk Factors to Specific Therapies

Luigi Lorini et al.

Summary: Oral potentially malignant disorders (OPMDs) are a group of oral mucosal diseases that have the potential to develop into oral squamous cell carcinoma (OSCC). Early diagnosis is crucial for improving survival rates. The focus is on early detection techniques and the effectiveness of treatments.

CANCERS (2021)

Article Health Care Sciences & Services

Improving Risk Identification of Adverse Outcomes in Chronic Heart Failure Using SMOTE plus ENN and Machine Learning

Ke Wang et al.

Summary: This study aimed to develop models with good identification for adverse outcomes in patients with heart failure (HF) and identify strong factors affecting prognosis. The combination of SMOTE+ENN and advanced machine learning methods significantly improved discrimination efficacy of adverse outcomes in HF patients, accurately stratified patients at risk of adverse outcomes, and identified the most significant factors leading to adverse outcomes.

RISK MANAGEMENT AND HEALTHCARE POLICY (2021)

Review Dentistry, Oral Surgery & Medicine

Capsaicin intake and oral carcinogenesis: A systematic review

Andrea Mosqueda-Solis et al.

Summary: Studies have shown that capsaicin is a chemopreventive agent that can prevent the development of oral cancer by inhibiting malignant cell proliferation and promoting apoptosis. However, more human studies are needed to clarify the real link between capsaicin intake and the prevalence of oral cancer.

MEDICINA ORAL PATOLOGIA ORAL Y CIRUGIA BUCAL (2021)

Review Otorhinolaryngology

Potentially malignant disorders of the oral cavity and oral dysplasia: A systematic review and meta-analysis of malignant transformation rate by subtype

Oreste Iocca et al.

HEAD AND NECK-JOURNAL FOR THE SCIENCES AND SPECIALTIES OF THE HEAD AND NECK (2020)

Review Dentistry, Oral Surgery & Medicine

Search less, verify more-Reviewing salivary biomarkers in oral cancer detection

John Adeoye et al.

JOURNAL OF ORAL PATHOLOGY & MEDICINE (2020)

Review Otorhinolaryngology

Impact of Time to Diagnosis and Treatment in Head and Neck Cancer: A Systematic Review

Henrieke W. Schutte et al.

OTOLARYNGOLOGY-HEAD AND NECK SURGERY (2020)

Article Computer Science, Information Systems

Comparison of supervised machine learning classification techniques in prediction of locoregional recurrences in early oral tongue cancer

Rasheed Omobolaji Alabi et al.

INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS (2020)

Article Dentistry, Oral Surgery & Medicine

Machine learning and treatment outcome prediction for oral cancer

Chui S. Chu et al.

JOURNAL OF ORAL PATHOLOGY & MEDICINE (2020)

Review Medicine, General & Internal

New Insights into Oral Cancer-Risk Factors and Prevention: A Review of Literature

Soussan Irani

INTERNATIONAL JOURNAL OF PREVENTIVE MEDICINE (2020)

Review Dentistry, Oral Surgery & Medicine

Alcohol-based mouthwash as a risk factor of oral cancer: A systematic review

Marina Ustrell-Borras et al.

MEDICINA ORAL PATOLOGIA ORAL Y CIRUGIA BUCAL (2020)

Editorial Material Biochemical Research Methods

POINTS OF SIGNIFICANCE Statistics versus machine learning

Danilo Bzdok et al.

NATURE METHODS (2018)

Article Dentistry, Oral Surgery & Medicine

The changing epidemiology of oral cancer: definitions, trends, and risk factors

D. I. Conway et al.

BRITISH DENTAL JOURNAL (2018)

Article Public, Environmental & Occupational Health

HPV-based cervical cancer screening-facts, fiction, and misperceptions

Nicolas Wentzensen et al.

PREVENTIVE MEDICINE (2017)

Review Oncology

The role of chronic mucosal trauma in oral cancer: A review of literature

Hitesh Rajendra Singhvi et al.

INDIAN JOURNAL OF MEDICAL AND PAEDIATRIC ONCOLOGY (2017)

Article Oncology

Detection of cancer through exhaled breath: a systematic review

Agne Krilaviciute et al.

ONCOTARGET (2015)

Review Health Policy & Services

Early detection and diagnosis of oral cancer: Strategies for improvement

P. J. Ford et al.

JOURNAL OF CANCER POLICY (2013)

Proceedings Paper Automation & Control Systems

Classifiers selection for ensemble learning based on accuracy and diversity

Liying Yang

CEIS 2011 (2011)

Review Oncology

Global epidemiology of oral and oropharyngeal cancer

Saman Warnakulasuriya

ORAL ONCOLOGY (2009)

Article Otorhinolaryngology

The association of smoking, alcoholic consumption, betel quid chewing and oral cavity cancer: a cohort study

Tin-Tin Yen et al.

EUROPEAN ARCHIVES OF OTO-RHINO-LARYNGOLOGY (2008)

Article Oncology

Family history and the risk of oral and pharyngeal

Werner Garavello et al.

INTERNATIONAL JOURNAL OF CANCER (2008)

Review Dentistry, Oral Surgery & Medicine

Natural history of potentially malignant oral lesions and conditions: an overview of the literature

Seamus S. Napier et al.

JOURNAL OF ORAL PATHOLOGY & MEDICINE (2008)

Review Dentistry, Oral Surgery & Medicine

Nomenclature and classification of potentially malignant disorders of the oral mucosa

S. Warnakulasuriya et al.

JOURNAL OF ORAL PATHOLOGY & MEDICINE (2007)

Review Oncology

Oral cancer treatment: developments in chemotherapy and beyond

VJ O'Neill et al.

BRITISH JOURNAL OF CANCER (2002)