BELUGA WHALE LION OPTIMIZATION IN DEEP-NETS FOR HUMAN AGE ESTIMATION USING HAND X-RAY

Biomedical Engineering Applications Basis and Communications, Год журнала: 2024, Номер 36(04)

Опубликована: Июль 10, 2024

Bones undergo significant changes in size and shape with the growth of child, bone age estimation is crucial for determining growth, genetic endocrine disorders children. Hand X-ray images are extensively utilized diagnosing The variation chronological indicates presence disorders, problems, abnormalities. Traditionally, estimated manually by inspecting images, which extremely time-consuming prone to error. Further, accuracy estimate depends on experience medical practitioner, thus it suffers from intra- inter-observer variability. Hence, overcome these issues, essential devise automatic methods that can high a short duration. In this work, using Deep Residual Network (DRN), whose learnable factors adjusted devised Beluga Whale Lion Optimization (BWLO) algorithm. BWLO_DRN examined its superiority considering metrics, like accuracy, True Positive Rate (TPR), Negative (TNR), corresponding values 89.8%, 86.8%, 90% found be achieved experimental results.

Язык: Английский

---

Using Support Vector Machines for Enhancing Cancer Prediction in Recommender Systems

Advances in Science, Technology & Innovation/Advances in science, technology & innovation, Год журнала: 2024, Номер unknown, С. 133 - 140

Опубликована: Янв. 1, 2024

Язык: Английский

---

Understanding the Minimal Clinically Viable Solutions for Disease Diagnosis and Prognosis via the Integration of AI-Powered Intelligent Systems

Advances in medical diagnosis, treatment, and care (AMDTC) book series, Год журнала: 2024, Номер unknown, С. 113 - 140

Опубликована: Июнь 30, 2024

This chapter explores the transformative impact of artificial intelligence (AI) on healthcare, with a focus illness diagnosis and prognosis, led by Luca Parisi's pioneering research. Parisi advocates for developing clinically viable solutions diseases, integrating machine learning (ML) evolutionary algorithms to improve clinical decision support systems (CDSS). Emphasis is placed interpretability trustworthiness. The research underscores AI's potential revolutionize decision-making, enhancing patient care outcomes. It contributes advancing green AI-powered intelligent disease filling literature gaps promoting minimal enrich efficacy.

Язык: Английский

---

Ontological modeling with recursive recurrent neural network and crayfish optimization for reliable breast cancer prediction

Biomedical Signal Processing and Control, Год журнала: 2024, Номер 99, С. 106810 - 106810

Опубликована: Сен. 12, 2024

Язык: Английский

---

PERS: Personalized environment recommendation system based on vital signs

Egyptian Informatics Journal, Год журнала: 2024, Номер 28, С. 100580 - 100580

Опубликована: Ноя. 29, 2024

Язык: Английский

---