On-line title: Use of Laser photobiomodulation in the treatment of Trigeminal Neuralgia: case series

Authors:
Marleny Elizabeth Márquez de Martínez Gerbi – PhD-FOP/UPE
TEAM:
Maria Regina Almeida de Menezes – PhD-FOP/UPE
Lara Marques Magalhães Moreno – PhD Student-FOP/UPE
Jéssica Meirinhos Miranda – PhD Student-FOP/UPE
Mavio Eduardo Bispo – CEO VIZIOMED
Márcia Bezerra da Silva – PhD – UFPE
Miranildo Daniel da Silva Júnior – Graduate Eng. Student-POLI/UP
Aldo Brugnera Júnior – INCT – USP

Laser photobiomodulation is a therapeutic technique that uses low-intensity light to stimulate regeneration and repair of damaged tissues. When associated with research with mesenchymal stem cells from the umbilical cord, it becomes a tool that improves results and directly impacts regenerative medicine. In recent years, Artificial Intelligence (AI) has been increasingly applied in these types of research to help with data analysis in order to optimize the delivery time of results, increase assertiveness, and reduce operating costs. The objective of this study was to analyze the impact of the use of AI in research with laser photobiomodulation associated with research on mesenchymal stem cells from the umbilical condon. The methodology used involved the review of recent studies that explored the application of AI in therapies with laser photobiomodulation and umbilical cord mesenchymal stem cells. The results indicated that AI can help to improve the precision and effectiveness of laser photobiomodulation treatments and, when associated with stem cell research, it helps to identify important images, patterns, genes and proteins. It quantifies and characterizes cell morphology and activity. It analyzes genomic data and identifies genes and signaling pathways involved in cell differentiation and regeneration. Improves understanding of stem cell behavior and its interaction with the environment.The relevance and benefits of applying AI in these researches is in helping to identify the best light sources to stimulate the regeneration of damaged tissues, optimizing treatment protocols for different injuries. High accuracy in the analysis and interpretation of data generated by surveys. Predict results accurately and enable the development of new treatments, in addition to developing smart and automated solutions efficiently and quickly. Improves the quality of health care. AI can also help predict treatment effectiveness in different patients and monitor treatment response over time. However, challenges were also discussed, such as the need to develop robust AI models and the ethical concern regarding the use of patient data. Future trends indicate that AI will continue to be an important tool in laser photobiomodulation research, and that new data analysis techniques can be developed to further improve the effectiveness of treatments. In conclusion, the application of AI in laser photobiomodulation research could have a significant impact on the effectiveness of treatments and understanding of underlying mechanisms. However, it is important to consider the challenges and ethical concerns associated with the use of AI in medicine and to ensure that AI models are developed responsibly and with consideration for patients’ rights.