{"doi":"10.1117/1.jbo.26.6.065003","title":"Mobile-based oral cancer classification for point-of-care screening","abstract":"SIGNIFICANCE: Oral cancer is among the most common cancers globally, especially in low- and middle-income countries. Early detection is the most effective way to reduce the mortality rate. Deep learning-based cancer image classification models usually need to be hosted on a computing server. However, internet connection is unreliable for screening in low-resource settings. AIM: To develop a mobile-based dual-mode image classification method and customized Android application for point-of-care oral cancer detection. APPROACH: The dataset used in our study was captured among 5025 patients with our customized dual-modality mobile oral screening devices. We trained an efficient network MobileNet with focal loss and converted the model into TensorFlow Lite format. The finalized lite format model is ∼16.3 MB and ideal for smartphone platform operation. We have developed an Android smartphone application in an easy-to-use format that implements the mobile-based dual-modality image classification approach to distinguish oral potentially malignant and malignant images from normal/benign images. RESULTS: We investigated the accuracy and running speed on a cost-effective smartphone computing platform. It takes ∼300 ms to process one image pair with the Moto G5 Android smartphone. We tested the proposed method on a standalone dataset and achieved 81% accuracy for distinguishing normal/benign lesions from clinically suspicious lesions, using a gold standard of clinical impression based on the review of images by oral specialists. CONCLUSIONS: Our study demonstrates the effectiveness of a mobile-based approach for oral cancer screening in low-resource settings.","journal":"Journal of Biomedical Optics","year":2021,"id":154688,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":62,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9633,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":291690,"name":"Sumsum P. Sunny","orcid":"0000-0001-9488-7615","position":1,"is_corresponding":false},{"id":480647,"name":"Shaobai Li","orcid":"0000-0001-5121-1607","position":2,"is_corresponding":false},{"id":656120,"name":"Keerthi Gurushanth","orcid":null,"position":3,"is_corresponding":false},{"id":656121,"name":"Pramila Mendonca","orcid":null,"position":4,"is_corresponding":false},{"id":656122,"name":"Nirza Mukhia","orcid":null,"position":5,"is_corresponding":false},{"id":654295,"name":"Sanjana Patrick","orcid":null,"position":6,"is_corresponding":false},{"id":654298,"name":"Shubha Gurudath","orcid":null,"position":7,"is_corresponding":false},{"id":654297,"name":"Subhashini Raghavan","orcid":null,"position":8,"is_corresponding":false},{"id":656123,"name":"Tsusennaro Imchen","orcid":null,"position":9,"is_corresponding":false},{"id":656124,"name":"Shirley T. Leivon","orcid":null,"position":10,"is_corresponding":false},{"id":656125,"name":"Trupti Kolur","orcid":null,"position":11,"is_corresponding":false},{"id":653333,"name":"Vivek Shetty","orcid":"0000-0002-9171-7319","position":12,"is_corresponding":false},{"id":656126,"name":"Vidya Bushan","orcid":null,"position":13,"is_corresponding":false},{"id":656127,"name":"Rohan Michael Ramesh","orcid":null,"position":14,"is_corresponding":false},{"id":655300,"name":"Natzem Lima","orcid":"0000-0002-3668-4374","position":15,"is_corresponding":false},{"id":653332,"name":"Vijay Pillai","orcid":"0000-0002-3923-9348","position":16,"is_corresponding":false},{"id":247928,"name":"Petra Wilder‐Smith","orcid":"0000-0002-7580-2409","position":17,"is_corresponding":false},{"id":655301,"name":"Alben Sigamani","orcid":"0000-0002-6927-1947","position":18,"is_corresponding":false},{"id":291697,"name":"Amritha Suresh","orcid":"0000-0002-0785-0054","position":19,"is_corresponding":false},{"id":653336,"name":"Moni Abraham Kuriakose","orcid":"0000-0001-7861-9741","position":20,"is_corresponding":false},{"id":291696,"name":"Praveen Birur","orcid":"0000-0001-5287-8323","position":21,"is_corresponding":false},{"id":341980,"name":"Rongguang Liang","orcid":"0000-0003-2792-3457","position":22,"is_corresponding":false},{"id":488635,"name":"Bofan Song","orcid":"0000-0002-1171-8478","position":0,"is_corresponding":true}],"reference_count":33,"raw_metadata":null,"created_at":"2026-07-18T23:43:54.469024Z","pmid":"34164967","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}