DATA DRIVEN HEARTS - AI and ML in CARDIOVASCULAR CARE

The book "Data Driven Hearts: AI and ML in Cardiovascular Care" explores the relationship between cutting-edge technology and cardiovascular care, emphasizing how AI is revolutionizing the field. Understanding cardiovascular disorders, risk factors, pathophysiology, and conventional diagnostic techniques are all covered. The book also explores the use of AI in medical imaging for cardiovascular diagnosis, predictive analytics in risk assessment, and data collecting and preprocessing.The diagnostic utility of electrocardiography (ECG), data preprocessing, classification of arrhythmias, and the possibility of continuous monitoring via tele-ECG are covered. Challenges, computational screening, virtual drug design, target identification, the function of clinical trials, and drug repurposing are also covered, in addition to personalized therapy suggestions.The ethical implications of AI and ML in healthcare are also covered in the book, along with issues related to patient privacy, legal frameworks, and the function of medical ethics committees.

Autorentext

La dottoressa Shruti Awasthi è una biochimica esperta con oltre 18 anni di esperienza nella ricerca e nel mondo accademico. Ha conseguito un dottorato di ricerca in biochimica medica e ha pubblicato molto, tra cui sette libri e 45 articoli di ricerca. Ha ricevuto numerosi premi, tra cui il "Young Scientist Award" nel 2012 e 12 medaglie d'oro per le sue presentazioni.

Klappentext

The book "Data Driven Hearts: AI and ML in Cardiovascular Care" explores the relationship between cutting-edge technology and cardiovascular care, emphasizing how AI is revolutionizing the field. Understanding cardiovascular disorders, risk factors, pathophysiology, and conventional diagnostic techniques are all covered. The book also explores the use of AI in medical imaging for cardiovascular diagnosis, predictive analytics in risk assessment, and data collecting and preprocessing.The diagnostic utility of electrocardiography (ECG), data preprocessing, classification of arrhythmias, and the possibility of continuous monitoring via tele-ECG are covered. Challenges, computational screening, virtual drug design, target identification, the function of clinical trials, and drug repurposing are also covered, in addition to personalized therapy suggestions.The ethical implications of AI and ML in healthcare are also covered in the book, along with issues related to patient privacy, legal frameworks, and the function of medical ethics committees.