Dataset Information

Recent Advances and Future Challenges in Pancreatic Cancer Care: Early Detection, Liquid Biopsies, Precision Medicine and Artificial Intelligence.

ABSTRACT: The incidence of pancreatic ductal adenocarcinoma (PDAC) is rising. While surgical techniques and peri-operative care have improved, the overall survival for PDAC remains poor. Thus, novel and bold research initiatives are needed along the spectrum of clinical care, a few of which will be discussed in this article. Early detection is crucial, with specific high-risk groups possibly benefiting from targeted screening programs. Liquid biopsies (such as circulating exosomes, tumor DNA, or tumor cells) offer promise as multifunctional biomarkers for early detection, treatment guidance, and recurrence monitoring. Precision medicine is being explored via targeted therapies for actionable mutations, such as PARP inhibitors for BRCA mutations, and immunotherapy strategies. Artificial intelligence (AI) is emerging as a powerful tool in medical imaging, biomarker discovery, genetics research, and treatment planning, and it can aid in diagnosis, treatment selection, and patient monitoring. However, its associated challenges include ethics, data security, algorithm reliability, and validation. Collaborative efforts between medical professionals, researchers, and AI experts are vital for unlocking AI's potential to enhance pancreatic cancer care. In conclusion, despite the challenges, advancements in liquid biopsies, precision medicine, and AI offer hope for enhancing the diagnosis, treatment, and management of pancreatic cancer.

SUBMITTER: Daamen LA

PROVIDER: S-EPMC10707510 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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Recent Advances and Future Challenges in Pancreatic Cancer Care: Early Detection, Liquid Biopsies, Precision Medicine and Artificial Intelligence.

Daamen Lois A LA Molenaar I Quintus IQ Groot Vincent P VP

Journal of clinical medicine 20231204 23

The incidence of pancreatic ductal adenocarcinoma (PDAC) is rising. While surgical techniques and peri-operative care have improved, the overall survival for PDAC remains poor. Thus, novel and bold research initiatives are needed along the spectrum of clinical care, a few of which will be discussed in this article. Early detection is crucial, with specific high-risk groups possibly benefiting from targeted screening programs. Liquid biopsies (such as circulating exosomes, tumor DNA, or tumor cel ...[more]

PMID: 38068536

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Project description:Precision medicine has the potential to revolutionize the way cardiovascular diseases are diagnosed, predicted, and treated by tailoring treatment strategies to the individual characteristics of each patient. Artificial intelligence (AI) has recently emerged as a promising tool for improving the accuracy and efficiency of precision cardiovascular medicine. In this scoping review, we aimed to identify and summarize the current state of the literature on the use of AI in precision cardiovascular medicine. A comprehensive search of electronic databases, including Scopes, Google Scholar, and PubMed, was conducted to identify relevant studies. After applying inclusion and exclusion criteria, a total of 28 studies were included in the review. We found that AI is being increasingly applied in various areas of cardiovascular medicine, including the diagnosis, prognosis of cardiovascular diseases, risk prediction and stratification, and treatment planning. As a result, most of these studies focused on prediction (50%), followed by diagnosis (21%), phenotyping (14%), and risk stratification (14%). A variety of machine learning models were utilized in these studies, with logistic regression being the most used (36%), followed by random forest (32%), support vector machine (25%), and deep learning models such as neural networks (18%). Other models, such as hierarchical clustering (11%), Cox regression (11%), and natural language processing (4%), were also utilized. The data sources used in these studies included electronic health records (79%), imaging data (43%), and omics data (4%). We found that AI is being increasingly applied in various areas of cardiovascular medicine, including the diagnosis, prognosis of cardiovascular diseases, risk prediction and stratification, and treatment planning. The results of the review showed that AI has the potential to improve the performance of cardiovascular disease diagnosis and prognosis, as well as to identify individuals at high risk of developing cardiovascular diseases. However, further research is needed to fully evaluate the clinical utility and effectiveness of AI-based approaches in precision cardiovascular medicine. Overall, our review provided a comprehensive overview of the current state of knowledge in the field of AI-based methods for precision cardiovascular medicine and offered new insights for researchers interested in this research area.

Dataset Information

Recent Advances and Future Challenges in Pancreatic Cancer Care: Early Detection, Liquid Biopsies, Precision Medicine and Artificial Intelligence.

Publications

Recent Advances and Future Challenges in Pancreatic Cancer Care: Early Detection, Liquid Biopsies, Precision Medicine and Artificial Intelligence.

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