Artificial Intelligence in Healthcare

Early and reliable identification of cardiac disorders from Phonocardiogram (PCG) signals acquired from wearable biosensors is critical to support clinical decision making and reduce subjectivity in auscultation-based assessments. This study proposes a multi-stage hybrid feature selection-classification approach to in…

Cardiovascular diseases remain one of the leading causes of mortality worldwide, making early and reliable diagnosis a critical challenge for modern healthcare systems. In this study, a systematic comparative performance anal... | Find, read and cite all the research you need on Tech Science Press

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Sağlık alanında karar destek sistemlerinin gelişmesi için yapay zeka çözümleri kullanılmaktadır. Geliştirilen yaklaşımlar, verilerin temel özelliklerini yansıtan yapay hasta grupları oluşturulmasına olanak sağlamaktadır. Sentetik hasta modelleri gerçek hasta verilerinin istatiksel ve klinik özelliklerini taklit ederek…

Thyroid cancer causes tens of thousands of deaths every year in the world. Treatment of this disease is possible with today's medical conditions. However, as in other types of cancer, recurrence is possible. The Differentiated Thyroid Cancer Recurrence dataset, which includes data from 383 patients and was obtained fr…

Kalp ve damar hastalıkları, dünya genelinde en yüksek ölüm yüküne sahip hastalık grubudur. Bu çalışmada, kalp hastalığı tahmini için KNIME Analytics Platform üzerinde uçtan uca, kodsuz biçimde yapılandırılmış bir Açıklanabilir Yapay Zekâ (XAI) iş akışı geliştirilmiştir. UCI Cleveland Heart Disease veri seti üzerinde L…

Kalp ve damar hastalıkları, dünya genelinde en yüksek ölüm yüküne sahip hastalık grubudur. Bu çalışmada, kalp hastalığı tahmini için KNIME Analytics Platform üzerinde uçtan uca, kodsuz biçimde yapılandırılmış bir Açıklanabilir Yapay Zekâ (XAI) iş akışı geliştirilmiştir. UCI Cleveland Heart Disease veri seti üzerinde L…

Background and Objectives Anthropometric prediction and metabolic disorder screening require cost-effective solutions in resource-limited settings. We develop a convex-optimized neural network with embedded feature selection to establish quantitative relationships between body morphology and metabolic health. Methods…

Demand forecasting for medical and consumable supplies in healthcare institutions is a challenging problem due to irregular usage patterns, seasonality, sudden demand spikes, and data sparsity, and inaccurate forecasts may lead to stock-outs, excessive inventory costs, and disruptions in patient care. This study propo…

In this study, lung cancer—related individual and environmental risk factors were analyzed using a Decision Tree–based machine learning approach. Two open-access datasets (“survey lung cancer.csv” and “lung-cancer.data”) were utilized. Since the survey dataset does not contain a direct clinical diagnosis label, the “S…

Poster presented at the SCA/HPCAsia2026 Conference. The publication is related to the benchmarking on analytics pipeline and querying capability of AQIS. The presented study includes benchmarking for providing efficinecy for analytics pipelines under increasing data size.