scholarly journals Evolving Paradigm of Precision Medicine in Cardiovascular Disease.

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Manish Narang ◽  
Ramanpreet Walia ◽  
Upendra Kaul ◽  
Krishnakutty Sudhir
Keyword(s):  
Artificial Intelligence ◽  
Cardiovascular Diseases ◽  
Precision Medicine ◽  
Interventional Cardiology ◽  
Genome Project ◽  
Johns Hopkins Hospital ◽  
Preventative Measures ◽  
Canadian Physician ◽  
The Right ◽  
William Osler

In the year 1892, Sir William Osler, the legendary Canadian physician and one of the four founding professors of Johns Hopkins Hospital, said “If it were not for the great variability among individuals, medicine might as well be a science and not an art”. It is this heterogeneity among patients with seemingly homogenous medical conditions, that form the basis of what we today refer to as precision medicine. The fundamental of precision medicine is based on the tenets of ‘The right drug for the right patient at the right time’. Personalized or precision medicine found immense popularity in oncology. With the completion of Human Genome Project and the advent of genomics, big data and artificial intelligence, 21st century saw rapid progress of precision medicine in predicting, diagnosing and treating cancer. However, the same has not happened to cardiovascular diseases, the biggest killer of humanity. In this review article, we aim to address the concepts, components, outcomes and applications of precision medicine in general, and to review the evolving paradigm of how precision medicine is shaping the management of cardiovascular diseases. We delve deep into the aspects of risk prediction, preventative measures, and targeted therapeutic approaches for cardiovascular diseases. We also look at the recent trends and current applications of precision medicine in this area, the problems they solve and the challenges they possess, and what is in store for the future. Finally, we review the application of artificial intelligence specific to cardiovascular diseases, and the role of precision medicine in interventional cardiology.

scholarly journals In Search of a Unifying Concept in Human Diseases

Diseases ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 68
Author(s):  
James Trosko
Keyword(s):  
Artificial Intelligence ◽  
Precision Medicine ◽  
New Technologies ◽  
Genome Project ◽  
Human Diseases ◽  
Therapeutic Benefits ◽  
History Of ◽  
Biological Discovery ◽  
Definition Of ◽  
The Human Genome Project

Throughout the history of biological/medicine sciences, there has been opposing strategies to find solutions to complex human disease problems. Both empirical and deductive approaches have led to major insights and concepts that have led to practical preventive and therapeutic benefits for the human population. The classic definitions of “science” (to know) has been paired with the classic definition of technology (to do). One knew more as the technology developed, and that development was often based on science. In other words, one could do more if science could improve the technology. In turn, this made possible to know more science with improved technology. However, with the development of new technologies of today in biology and medicine, major advances have been made, such as the information from the Human Genome Project, genetic engineering techniques and the use of bioinformatic uses of sophisticated computer analyses. This has led to the renewed idea that Precision Medicine, while raising some serious ethical concerns, also raises the expectation of improved potential of risk predictions for prevention and treatment of various genetically and environmentally influenced human diseases. This new field Artificial Intelligence, as a major handmaiden to Precision Medicine, is significantly altering the fundamental means of biological discovery. However, can today’s fundamental premise of “Artificial Intelligence”, based on identifying DNA, as the primary nexus of human health and disease, provide the practical solutions to complex human diseases that involve the interaction of those genes with the broad spectrum of “environmental factors”? Will it be “precise” enough to provide practical solutions for prevention and treatments of diseases? In this “Commentary”, with the example of human carcinogenesis, it will be challenged that, without the integration of mechanistic and hypothesis-driven approaches with the “unbiased” empirical analyses of large numbers of data, the Artificial Intelligence approach with fall short.

scholarly journals Computational Simulator Models and Invasive Hemodynamic Monitoring as Tools for Precision Medicine in Pulmonary Arterial Hypertension

2021 ◽  
Vol 11 (1) ◽  
pp. 82
Author(s):  
Giovanna Manzi ◽  
Cristiano Miotti ◽  
Marco Valerio Mariani ◽  
Silvia Papa ◽  
Federico Luongo ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Pulmonary Arterial Hypertension ◽  
Arterial Hypertension ◽  
Precision Medicine ◽  
Computational Models ◽  
Therapeutic Strategy ◽  
Tailored Treatment ◽  
Invasive Hemodynamic Monitoring ◽  
Pulmonary Arterial ◽  
The Right

Precision medicine, providing the right therapeutic strategy for the right patient, could revolutionize management and prognosis of patients affected by cardiovascular diseases. Big data and artificial intelligence are pivotal for the realization of this ambitious design. In the setting of pulmonary arterial hypertension (PAH), the use of computational models and data derived from ambulatory implantable hemodynamic monitors could provide useful information for tailored treatment, as requested by precision medicine.

scholarly journals Epigenetics Analysis and Integrated Analysis of Multiomics Data, Including Epigenetic Data, Using Artificial Intelligence in the Era of Precision Medicine

Biomolecules ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 62 ◽  
Author(s):  
Ryuji Hamamoto ◽  
Masaaki Komatsu ◽  
Ken Takasawa ◽  
Ken Asada ◽  
Syuzo Kaneko
Keyword(s):  
Artificial Intelligence ◽  
Genetic Variation ◽  
Precision Medicine ◽  
Large Scale ◽  
Human Cancer ◽  
Genomic Medicine ◽  
Disease Onset ◽  
Genome Project ◽  
Integrated Analysis ◽  
Wide Range

To clarify the mechanisms of diseases, such as cancer, studies analyzing genetic mutations have been actively conducted for a long time, and a large number of achievements have already been reported. Indeed, genomic medicine is considered the core discipline of precision medicine, and currently, the clinical application of cutting-edge genomic medicine aimed at improving the prevention, diagnosis and treatment of a wide range of diseases is promoted. However, although the Human Genome Project was completed in 2003 and large-scale genetic analyses have since been accomplished worldwide with the development of next-generation sequencing (NGS), explaining the mechanism of disease onset only using genetic variation has been recognized as difficult. Meanwhile, the importance of epigenetics, which describes inheritance by mechanisms other than the genomic DNA sequence, has recently attracted attention, and, in particular, many studies have reported the involvement of epigenetic deregulation in human cancer. So far, given that genetic and epigenetic studies tend to be accomplished independently, physiological relationships between genetics and epigenetics in diseases remain almost unknown. Since this situation may be a disadvantage to developing precision medicine, the integrated understanding of genetic variation and epigenetic deregulation appears to be now critical. Importantly, the current progress of artificial intelligence (AI) technologies, such as machine learning and deep learning, is remarkable and enables multimodal analyses of big omics data. In this regard, it is important to develop a platform that can conduct multimodal analysis of medical big data using AI as this may accelerate the realization of precision medicine. In this review, we discuss the importance of genome-wide epigenetic and multiomics analyses using AI in the era of precision medicine.

Artificial Intelligence as a Business Partner in Cardiovascular Precision Medicine: an Emerging Approach for Disease Detection and Treatment Optimization

2020 ◽  
Vol 28 ◽  
Author(s):  
Valeria Visco ◽  
Germano Junior Ferruzzi ◽  
Federico Nicastro ◽  
Nicola Virtuoso ◽  
Albino Carrizzo ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Heart Failure ◽  
Atrial Fibrillation ◽  
Precision Medicine ◽  
Clinical Decision Making ◽  
Disease Detection ◽  
Physician Patient Relationship ◽  
Invasive Approach ◽  
Tailored Treatment ◽  
The Impact

Background: In the real world, medical practice is changing hand in hand with the development of new Artificial Intelligence (AI) systems and problems from different areas have been successfully solved using AI algorithms. Specifically, the use of AI techniques in setting up or building precision medicine is significant in terms of the accuracy of disease discovery and tailored treatment. Moreover, with the use of technology, clinical personnel can deliver a very much efficient healthcare service. Objective: This article reviews AI state-of-the-art in cardiovascular disease management, focusing on diagnostic and therapeutic improvements. Methods: To that end, we conducted a detailed PubMed search on AI application from distinct areas of cardiology: heart failure, arterial hypertension, atrial fibrillation, syncope and cardiovascular rehabilitation. Particularly, to assess the impact of these technologies in clinical decision-making, this research considers technical and medical aspects. Results: On one hand, some devices in heart failure, atrial fibrillation and cardiac rehabilitation represent an inexpensive, not invasive or not very invasive approach to long-term surveillance and management in these areas. On the other hand, the availability of large datasets (big data) is a useful tool to predict the development and outcome of many cardiovascular diseases. In summary, with this new guided therapy, the physician can supply prompt, individualised, and tailored treatment and the patients feel safe as they are continuously monitored, with a significant psychological effect. Conclusion: Soon, tailored patient care via telemonitoring can improve the clinical practice because AI-based systems support cardiologists in daily medical activities, improving disease detection and treatment. However, the physician-patient relationship remains a pivotal step.

scholarly journals Beyond Last Words: Patterns of Linguistic and Interactional Behavior in a Historical Sample of Dying Hospital Patients

2021 ◽  
pp. 003022282110009
Author(s):  
Michael Erard
Keyword(s):  
Clinical Study ◽  
Social Context ◽  
Small Step ◽  
Left Behind ◽  
The Social ◽  
Canadian Physician ◽  
Hospital Patients ◽  
Historical Sample ◽  
William Osler ◽  
Frequent Observation

Patterns of linguistic and interactional behavior by people at the very end of their lives are not well described, partly because data is difficult to obtain. This paper analyzes descriptions of 486 deaths gathered from 1900 to 1904 in the first-ever clinical study of dying by noted Canadian physician, Sir William Osler. Only 16 patients were noted speaking, and only four canonical last words were reported. The most frequent observation by medical staff was that the deaths were quiet ( n = 30), though range of other behaviors were noted (e.g., moaning, delirium, seeming intention to speak). Osler's problematic study left behind data whose analysis is a small step toward empirically characterizing the linguistic and interactional details of a previously under-described phenomena as well as the importance of the social context in which they occur.

scholarly journals Will Artificial Intelligence Replace the Movement Disorders Specialist for Diagnosing and Managing Parkinson’s Disease?

2021 ◽  
pp. 1-6
Author(s):  
Matt Landers ◽  
Suchi Saria ◽  
Alberto J. Espay
Keyword(s):  
Artificial Intelligence ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Precision Medicine ◽  
Movement Disorders ◽  
Living Environment ◽  
Patient Status ◽  
Patient Symptom ◽  
Molecular Therapies ◽  
Improve Patient

The use of artificial intelligence (AI) to help diagnose and manage disease is of increasing interest to researchers and clinicians. Volumes of health data are generated from smartphones and ubiquitous inexpensive sensors. By using these data, AI can offer otherwise unobtainable insights about disease burden and patient status in a free-living environment. Moreover, from clinical datasets AI can improve patient symptom monitoring and global epidemiologic efforts. While these applications are exciting, it is necessary to examine both the utility and limitations of these novel analytic methods. The most promising uses of AI remain aspirational. For example, defining the molecular subtypes of Parkinson’s disease will be assisted by future applications of AI to relevant datasets. This will allow clinicians to match patients to molecular therapies and will thus help launch precision medicine. Until AI proves its potential in pushing the frontier of precision medicine, its utility will primarily remain in individualized monitoring, complementing but not replacing movement disorders specialists.

scholarly journals Application of Artificial Intelligence for Medical Research

Biomolecules ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 90
Author(s):  
Ryuji Hamamoto
Keyword(s):  
Artificial Intelligence ◽  
Medical Research ◽  
Human Genome ◽  
21St Century ◽  
Human Genome Project ◽  
Genome Project ◽  
International Consortium ◽  
The Human Genome Project

The Human Genome Project, completed in 2003 by an international consortium, is considered one of the most important achievements for mankind in the 21st century [...]

P2Y12 inhibitors in neuroendovascular surgery: An opportunity for precision medicine

2021 ◽  
pp. 159101992199139
Author(s):  
Axel Rosengart ◽  
Malie K Collins ◽  
Philipp Hendrix ◽  
Ryley Uber ◽  
Melissa Sartori ◽  
...  
Keyword(s):  
Adverse Events ◽  
Precision Medicine ◽  
Point Of Care ◽  
Indirect Evidence ◽  
Cost Benefit ◽  
Interventional Cardiology ◽  
Platelet Inhibition ◽  
Response Monitoring ◽  
P2y12 Inhibitor ◽  
P2y12 Inhibitors

Introduction Dual antiplatelet therapy (DAPT), primarily the combination of aspirin with a P2Y12 inhibitor, in patients undergoing intravascular stent or flow diverter placement remains the primary strategy to reduce device-related thromboembolic complications. However, selection, timing, and dosing of DAPT is critical and can be challenging given the existing significant inter- and intraindividual response variations to P2Y12 inhibitors. Methods Assessment of indexed, peer-reviewed literature from 2000 to 2020 in interventional cardiology and neuroendovascular therapeutics with critical, peer-reviewed appraisal and extraction of evidence and strategies to utilize DAPT in cardio- and neurovascular patients with endoluminal devices. Results Both geno- and phenotyping for DAPT are rapidly and conveniently available as point-of-care testing at a favorable cost-benefit ratio. Furthermore, systematic inclusion of a quantifying clinical risk score combined with an operator-linked, technical risk assessment for potential adverse events allows a more precise and individualized approach to new P2Y12 inhibitor therapy. Conclusions The latest evidence, primarily obtained from cardiovascular intervention trials, supports that combining patient pharmacogenetics with drug response monitoring, as part of an individually tailored, precision medicine approach, is both predictive and cost-effective in achieving and maintaining individual target platelet inhibition levels. Indirect evidence supports that this gain in optimizing drug responses translates to reducing main adverse events and overall treatment costs in patients undergoing DAPT after intracranial stent or flow diverting treatment.

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