The Application of tDCS to Treat Pain and Psychocognitive Symptoms in Cancer Patients: A Scoping Review.

Background: The use of transcranial direct current stimulation (tDCS) to modulate pain, psychological aspects, and cognitive functions has increased in recent years. The present scoping review aims to investigate the use of tDCS in cancer patients and its significant impact on psychocognitive and pain related symptoms. Methods: From the earliest available date to June 2023, a comprehensive search was conducted in three electronic scientific databases-PubMed, Scopus, and Embase-and other supplementary sources. Ten relevant studies were identified and included, comprising single case studies, randomized controlled trials, pilot studies, and one retrospective study. PRISMA guidelines for scoping reviews were followed. Results: These studies investigated the use of tDCS to improve pain and psychocognitive aspects in patients with various types of cancer, including breast, oral, bladder, lung, pancreatic, head and neck cancer, hepatocellular carcinoma, and meningioma. Overall, the results suggest that tDCS has shown efficacy in relieving pain, reducing anxiety and depression, and improving cognitive function in cancer patients. Conclusion: Due to the limited number and high heterogeneity of the existing literature in this field, more investigation and the establishment of standardized protocols would be required to obtain more conclusive evidence.

Patients' Perceptions and Attitudes to the Use of Artificial Intelligence in Breast Cancer Diagnosis: A Narrative Review.

Breast cancer remains the most prevalent cancer among women worldwide, necessitating advancements in diagnostic methods. The integration of artificial intelligence (AI) into mammography has shown promise in enhancing diagnostic accuracy. However, understanding patient perspectives, particularly considering the psychological impact of breast cancer diagnoses, is crucial. This narrative review synthesizes literature from 2000 to 2023 to examine breast cancer patients' attitudes towards AI in breast imaging, focusing on trust, acceptance, and demographic influences on these views. Methodologically, we employed a systematic literature search across databases such as PubMed, Embase, Medline, and Scopus, selecting studies that provided insights into patients' perceptions of AI in diagnostics. Our review included a sample of seven key studies after rigorous screening, reflecting varied patient trust and acceptance levels towards AI. Overall, we found a clear preference among patients for AI to augment rather than replace the diagnostic process, emphasizing the necessity of radiologists' expertise in conjunction with AI to enhance decision-making accuracy. This paper highlights the importance of aligning AI implementation in clinical settings with patient needs and expectations, emphasizing the need for human interaction in healthcare. Our findings advocate for a model where AI augments the diagnostic process, underlining the necessity for educational efforts to mitigate concerns and enhance patient trust in AI-enhanced diagnostics.