Publications by authors named "K D Isuri Weerasinghe"

Background: Sports nutrition plays a crucial role in providing the fuel to meet the energy demands of athletes' training programmes, enhancing adaptations associated with training, and ensuring rapid recovery between workouts. However, evidence suggests that the dietary habits of many athletes are unsatisfactory when compared to sport-specific nutrition recommendations. This discrepancy is mainly due to a lack of up-to-date, evidence-based nutritional knowledge.

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This narrative review examines the transformative role of Artificial Intelligence (AI) and Machine Learning (ML) in organ retrieval and transplantation. AI and ML technologies enhance donor-recipient matching by integrating and analyzing complex datasets encompassing clinical, genetic, and demographic information, leading to more precise organ allocation and improved transplant success rates. In surgical planning, AI-driven image analysis automates organ segmentation, identifies critical anatomical features, and predicts surgical outcomes, aiding pre-operative planning and reducing intraoperative risks.

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In-vitro fertilization (IVF) has been a transformative advancement in assisted reproductive technology. However, success rates remain suboptimal, with only about one-third of cycles resulting in pregnancy and fewer leading to live births. This narrative review explores the potential of artificial intelligence (AI), machine learning (ML), and deep learning (DL) to enhance various stages of the IVF process.

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Organ transplantation is a critical medical procedure that saves and improves lives, yet the system faces significant challenges that result in many missed opportunities. This comprehensive review examines the factors contributing to these missed opportunities and the concerns of potential donors. The shortage of donors remains a major issue, exacerbated by low registration rates, family consent refusals, and strict medical and health criteria.

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: Cancer remains a leading cause of death worldwide. Progress in its effective treatment has been hampered by challenges in personalized therapy, particularly in patients with comorbid conditions. The integration of artificial intelligence (AI) into patient profiling offers a promising approach to enhancing individualized anticancer therapy.

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