Harnessing the Potential of ChatGPT in Endodontics: A Comprehensive Review

Artificial intelligence, and particularly language models like ChatGPT, are increasingly transforming the field of healthcare, including dentistry and, more specifically, endodontics. This review explores the current and potential applications of ChatGPT in endodontics, addressing its impact on diagnosis, treatment planning, education, patient communication, research, and highlights challenges, ethical considerations, and future directions for leveraging ChatGPT to enhance the practice of endodontic

Non-invasive biomarkers for sperm retrieval in non-obstructive patients: a comprehensive review

Recent advancements in reproductive medicine have guided novel strategies for addressing male infertility, particularly in cases of non-obstructive azoospermia (NOA). Two prominent invasive interventions, namely testicular sperm extraction (TESE) and microdissection TESE (micro-TESE), have emerged as key techniques to retrieve gametes for assisted reproduction technologies (ART). Both heterogeneity and complexity of NOA pose a multifaceted challenge to clinicians, as the invasiveness of these procedures and their unpredictable success underscore the need for more precise guidance. Seminal plasma can be aptly regarded as a liquid biopsy of the male reproductive tract, encompassing secretions from the testes, epididymides, seminal vesicles, bulbourethral glands, and prostate. This fluid harbors a variety of cell-free nucleic acids, microvesicles, proteins, and metabolites intricately linked to gonadal activity. However, despite numerous investigations exploring potential biomarkers from seminal fluid, their widespread inclusion into the clinical practice remains limited. This could be partially due to the complex interplay of diverse clinical and genetic factors inherent to NOA that likely contributes to the absence of definitive biomarkers for residual spermatogenesis. It is conceivable that the integration of clinical data with biomarkers could increase the potential in predicting surgical procedure outcomes and their choice in NOA cases. This comprehensive review addresses the challenge of sperm retrieval in NOA through non-invasive biomarkers. Moreover, we delve into promising perspectives, elucidating innovative approaches grounded in multi-omics methodologies, including genomics, transcriptomics and proteomics. These cutting-edge techniques, combined with the clinical and genetics features of patients, could improve the use of biomarkers in personalized medical approaches, patient counseling, and the decision-making continuum. Finally, Artificial intelligence (AI) holds significant potential in the realm of combining biomarkers and clinical data, also in the context of identifying non-invasive biomarkers for sperm retrieval

Application of artificial intelligence for early detection of breast cancer

Breast cancer, the most common malignancy in women worldwide, demands early and accurate detection for optimal outcomes. The incorporation of artificial intelligence (AI) into breast cancer diagnostics offers a transformative approach, potentially revolutionising traditional mammography-based screening methods. AI, driven by algorithms and machine learning, holds the promise to identify patterns and anomalies with higher precision than conventional mammograms. While AI showcases advantages, such as enhanced image analysis and the potential for personalised diagnostics, it also has drawbacks. In its nascent stages, the technology faces challenges in terms of accuracy, variance, and data representativeness. Ethical considerations, especially concerning data privacy and patient consent, further complicate its implementation. Nonetheless, the future of AI in breast cancer diagnosis is promising, with ongoing research aimed at refining the technology and addressing its limitations. This fusion of AI with clinical expertise is expected to usher in an era of advanced, patient-centred breast cancer care.</p