Sign inSubmit
Tips: “quotes” for a phrase · author:Lee · a DOI goes straight to its article

23 results for “Medical Artificial Intelligence”
Set a search alert
Research ArticleOpen accessIn the keywordsHepatitis B Diagnosis Using Logical Inference and Self-Organizing MapGhumbre Shashikant Uttreshwar, A.A. GhatolDespite all the standardization efforts made, medical diagnosis is still regarded as an art owing to the fact that that medical diagnosis requires an expertise in handling the uncertainty which is unavailable in today's computing machinery. Though artificial intelligence is not a new concept it has been widely recognized as a new technology in computer science. Numerous areas such as … …Journal of Computer Science, Vol. 4, Issue 12 · 31 Dec 2008 · 6,874 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEvaluation of Language Models (LLMs) in the Interpretation of Tuberculosis Concepts: Design of a Virtual Assistant for Clinical Support and Patient EducationMauricio Acevedo-Carrillo, Shirley Fiorella Simbron EspejoTuberculosis (TB) remains a global public health challenge, where access to accurate and up-to-date information is crucial for professionals and patients. This research comparatively evaluated the performance of five language models (LLMs) Med-PaLM 2, GPT-4, MEDITRON-70B, Me-LLaMA, and Clinical Camel in the TB domain and implemented a mobile virtual assistant as a proof-of-concept based on the best-performing model. Clinical accuracy … …Journal of Computer Science, Vol. 22, Issue 9 · 30 Sep 2026 · 491 accessesView PDFCite
Review ArticleOpen accessIn the keywordsMachine Learning Advancements for Lung Cancer Detection: An In-Depth Review and Future ProspectsAanchal Vij, Kuldeep Singh Kaswan, Anand NayyarLung cancer is a major cause of cancer-related mortality globally, underscoring the necessity for efficient diagnostic instruments. The review paper summarizes the role of ML and DL in detection, staging, and prognostication of lung cancer. We evaluate the relative efficacy of several models, such as CNNs, SVMs, and ensemble approaches, by analyzing publically accessible imaging and molecular information. We emphasize … …Journal of Computer Science, Vol. 22, Issue 1 · 1 Mar 2026 · 1,794 accessesView PDFCite
Research ArticleOpen accessIn the abstractTransfer Learning-Driven Binary Classification of Chest X-ray for Pneumonia Using Deep Convolutional ArchitecturesNusrath Fathima, Pradeep KumarPneumonia is the most common infectious cause of lung inflammation, resulting from the presence of viruses or bacteria in the microscopic air sacs. In recent years, artificial intelligence, particularly deep learning, has gained significant traction in the field of medical imaging. Early detection and diagnosis of pneumonia using chest X-rays can support radiologists in clinical decision-making and subsequent treatment planning, … …Journal of Computer Science, Vol. 22, Issue 3 · 10 Mar 2026 · 1,542 accessesView PDFCite
Research ArticleOpen accessIn the abstractTowards an Explainable Approach: Hybrid Residual Network and SVM for Automated Brain Tumor Detection and ClassificationKamini Lamba, Shalli RaniThe abnormal growth of brain cells leads to tumor formation, which can be fatal if not detected and treated promptly. Given the complexity of brain tumors, early detection is critical in healthcare. Traditional radiology-based tumor detection is prone to human error and delays. Hence, a computer- assisted method is needed for accurate and efficient diagnosis. With the rapid advancements in … …Journal of Computer Science, Vol. 22, Issue 1 · 11 Feb 2026 · 1,427 accessesView PDFCite
Research ArticleOpen accessIn the abstractRefining Chest X-ray Interpretation with Deep Transfer Learning TechniquesR. Sriramkumar, K. Selvakumar, J. JeganChest X-rays are essential diagnostic tools for thoracic diseases, but different doctors' interpretations can differ greatly, which frequently results in inconsistent diagnoses. By using deep transfer learning techniques, this study seeks to improve the accuracy of Chest X-ray interpretations. More accurate and effective analysis can be accomplished with the growing potential of artificial intelligence (AI) in medical imaging, especially through … …Journal of Computer Science, Vol. 21, Issue 10 · 27 Nov 2025 · 2,644 accessesView PDFCite
Research ArticleOpen accessIn the abstractInteractivity in VR Therapy: Assessing Efficacy Across Acrophobia SeverityChiew Mei Chan, Soo See Chai, Kok Luong Goh, Sze Kiat SimVirtual Reality (VR) and Artificial Intelligence (AI) have gained popularity in medical treatments, including for acrophobia- a common but often untreated fear of heights. Traditional therapies are often expensive and complex, making VR therapy a convenient and safe alternative. This study evaluates the efficacy of an AI-augmented interactivity VR therapy for acrophobia, focusing on user satisfaction and treatment outcomes. Graded … …Journal of Computer Science, Vol. 21, Issue 5 · 16 Apr 2025 · 5,864 accessesView PDFCite
Research ArticleOpen accessIn the abstractFeature Extraction of Sit-to-Stand Transition Using Vision-Based Pose EstimationAchmad Rizal, Bayu Erfianto, Sugondo Hadiyoso, IstiqomahSit-to-Stand Transition (STS) and vice versa are important indicators of independence and physical health. For normal people, this movement is easy to do but can be difficult for people who have health problems, such as those who have had an injury or stroke. Sit-to-stand assessments can be used to detect spinal disorders. However, spinal kinematic measurements require special instrumentation and … …Journal of Computer Science, Vol. 21, Issue 3 · 21 Feb 2025 · 6,204 accessesView PDFCite
Research ArticleOpen accessIn the abstractAI-Based Feature Extraction Approaches for Dual Modalities of Autism Spectrum Disorder NeuroimagesMeenakshi Malviya, Chandra J, Nagendra NHigh-dimensional data, lower detection accuracy, susceptibility to manual errors, and the requirement of clinical experts are some drawbacks of conventional classification models available for Autism Spectrum Disorder (ASD) detection. To address these challenges and explore the affiliated information from advanced imaging modalities such as Magnetic Resonance Imaging (MRI) in structural MRI (sMRI) and resting state-functional MRI (rs-fMRI), the study applied … …Journal of Computer Science, Vol. 20, Issue 11 · 28 Sep 2024 · 5,087 accessesView PDFCite
Research ArticleOpen accessIn the abstractAI-Guided Anatomical Landmark and Abnormality Detection for Autonomous Endoscopy ExaminationMd Shakhawat Hossain, Munim Ahmed et al.Aabakken, L., Barkun, A. N., Cotton, P. B., Fedorov, E., Fujino, M. A., Ivanova, E., Kudo, S., Kuznetzov, K., De Lange, T., Matsuda, K., Moine, O., Rembacken, B., Rey, J., Romagnuolo, J., Rösch, T., Sawhney, M., Yao, K., & Waye, J. D. (2014). Standardized endoscopic reporting. Journal of Gastroenterology and Hepatology, 29(2), 234–240. https://doi.org/10.1111/jgh.12489 Aliyi, S., Dese, K., & Raj, … …Journal of Computer Science, Vol. 20, Issue 8 · 29 May 2024 · 6,783 accessesView PDFCite