Artificial intelligence in optimizing the prediction, diagnosis, and treatment of cardiovascular diseases

45^th Euro-Global Summit on Cancer Therapy & Radiation Oncology

November 27-28, 2023 Paris, France

Fangling Tu

Chongqing University Three Gorges Hospital, China

Scientific Tracks Abstracts: J Cancer Sci Ther

Abstract :

Objective: Cardiovascular diseases (CVDs) remain the leading cause of death globally, posing significant challenges to healthcare systems. The objective of this review is to explore how artificial intelligence (AI) can optimize the prediction, diagnosis, and treatment of CVDs, thereby improving patient outcomes and enhancing healthcare efficiency. Methods and Materials: This review synthesizes findings from various studies and applications of AI in the field of cardiovascular medicine. AI technologies discussed include machine learning algorithms, deep learning networks, and predictive analytics applied to patient data. The methods focus on AI's capabilities in processing large datasets, recognizing patterns, and making predictions that surpass traditional statistical approaches. Results: AI has demonstrated significant advancements in the field of cardiovascular health: Prediction: AI models have accurately predicted acute myocardial infarction with a sensitivity of over 90%. For instance, using features from electronic health records and ECG data, AI algorithms have reduced false negatives by 30% compared to traditional models. Diagnosis: In diagnosing CVDs through imaging, AI has achieved accuracy levels exceeding 95% when interpreting echocardiograms and MRI scans. Automated systems have reduced diagnostic times from hours to minutes, crucially speeding up the intervention process. Treatment: In treatment applications, AI-driven robotic surgeries have shown a 20% improvement in patient recovery times and a 15% reduction in complications. AI has also been instrumental in developing personalized medication plans, increasing the efficacy of treatments by tailoring them to individual genetic profiles. Conclusion: AI has profoundly impacted the field of cardiovascular medicine, offering substantial improvements over conventional methods in prediction, diagnosis, and treatment. The data-driven insights provided by AI not only enhance the accuracy and efficiency of cardiovascular disease diagnosis but also pave the way for personalized and predictive healthcare solutions. Continued integration of AI into cardiovascular disease diagnosis promises to further revolutionize this vital field, making it more adaptive, efficient, and patientfocused.

Biography :

Fangling Tu is affiliated to Chongqing University Three Gorges Hospital, China. She is a recipient of many awards and grants for her valuable contributions and discoveries in major area of subject research. Her international experience includes various programs, contributions and participation in different countries for diverse fields of study. Her research interests reflect in her wide range of publications in various national and international journals