The doctor will see you now: How machine learning and artificial intelligence can extend our understanding and treatment of asthma

Messinger, Amanda I.; Luo, Gang; Deterding, Robin R.

doi:10.1016/j.jaci.2019.12.898

Cited by 31 publications

(23 citation statements)

References 10 publications

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“…61 It will also be important to consider how the use of AI fits into clinical workflow (ie, everyday practice), and how issues of patient safety and physician liability should be addressed. Overall, AI is likely to play a key role in aiding clinicians in the diagnosis and differentiation of respiratory diseases in the future, 62 and it will be exciting to see the benefits that arise for the patients and doctors from its use in everyday clinical practice.…”

Section: Discussionmentioning

confidence: 99%

Artificial Intelligence/Machine Learning in Respiratory Medicine and Potential Role in Asthma and COPD Diagnosis

Kaplan

Cao

FitzGerald

et al. 2021

The Journal of Allergy and Clinical Immunology: In Practice

109

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Section: Discussionmentioning

confidence: 99%

Artificial Intelligence/Machine Learning in Respiratory Medicine and Potential Role in Asthma and COPD Diagnosis

Kaplan

Cao

FitzGerald

et al. 2021

The Journal of Allergy and Clinical Immunology: In Practice

109

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“…The human brain is simply not capable of recognising large amounts of longitudinal patterns and interactions between different predictors, as computers can. 18 For these reasons, AI can be promising especially when based on real-life large databases and when using ML techniques, for instance, by supporting healthcare providers in predicting the effect of specific treatment approaches. 19 In this way AI can be a valuable aid for healthcare professionals and reduce the risk of treatment side effects of patients.…”

Section: Health-risk Prediction For Asthma and Copdmentioning

confidence: 99%

Developing an ML pipeline for asthma and COPD: The case of a Dutch primary care service

Mariani

Metting

Lahr

et al. 2021

Int J of Intelligent Sys

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A complex combination of clinical, demographic and lifestyle parameters determines the correct diagnosis and the most effective treatment for asthma and Chronic Obstructive Pulmonary Disease patients. Artificial Intelligence techniques help clinicians in devising the correct diagnosis and designing the most suitable clinical pathway accordingly, tailored to the specific patient conditions. In the case of machine learning (ML) approaches, availability of real‐world patient clinical data to train and evaluate the ML pipeline deputed to assist clinicians in their daily practice is crucial. However, it is common practice to exploit either synthetic data sets or heavily preprocessed collections cleaning and merging different data sources. In this paper, we describe an automated ML pipeline designed for a real‐world data set including patients from a Dutch primary care service, and provide a performance comparison of different prediction models for (i) assessing various clinical parameters, (ii) designing interventions, and (iii) defining the diagnosis.

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“…28 Another example of AI usage is the recognition of cardiotoxic and non-cardiotoxic drugs belonging to the anticancer category by the usage of an AI algorithm. 29 Machine learning has also been explored for the identification of potential antibiotics from a list of 100 million molecules. Halicin is the first antibiotic to be identified using AI.…”

Section: Drug Discoverymentioning

confidence: 99%

The Beginning of a New Era: Artificial Intelligence in Healthcare

2020

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The healthcare sector is considered to be one of the largest and fast-growing industries in the world. Innovations and novel approaches have always remained the prime aims in order to bring massive development. Before the emergence of technology, all the sectors, including the healthcare sector was dependant dependent on man power, which was time-consuming, and less accurate with lack of efficiency. With the recent advancements in machine learning, the condition is has been steadily revolutionizing. in the practice of the health care industry. Artificial Intelligence intelligence (AI) lies in the computer science department, which stresses on the intelligent machines’ creation, that work and react just like human beings. In simple words, AI is the capability of a computer program to think and learn, almost satisfying natural intelligence. It is the ability of a system to interpret the external data correctly, learn from it and finally use those learnings to execute some particular goals and tasks through adaptation. It utilizes multiple technologies to comprehend, act and understand from past experiences. Involving AI is not a science fiction that was once a very long time ago. It AI being an emerging technology has been adopted in various facets of healthcare ranging from drug discovery to patient monitoring. rapidly penetrated its wings developed itself into almost all the industries. Irrespective of the person’s background, whether he/she is a student, industry worker, an entrepreneur, or a scientist, having basic knowledge about the importance and applications of AI would be impactful. Currently, the applications of AI has have been expanding into those fields, which was once thought to be the only domain of human expertise such as health care sector. In this review article, we have shedthrown light on the present usage of AI in the healthcare sector, such as its working, and the way this system is being implemented in different domains, such as drug discovery, diagnosis of diseases, clinical trials, remote patient monitoring, and nanotechnology. We have also slightlybriefly touched upon its applications in touching other sectors as well. The public opinions have also been analyszed and discussed along with the future prospects.The main goals have been briefed. prospects. We have discussed the Along with the merits, we have also discussed about and the other side of AI, i.e. the disadvantages of this as wellin the last part of the manuscript.

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The doctor will see you now: How machine learning and artificial intelligence can extend our understanding and treatment of asthma

Cited by 31 publications

References 10 publications

Artificial Intelligence/Machine Learning in Respiratory Medicine and Potential Role in Asthma and COPD Diagnosis

Artificial Intelligence/Machine Learning in Respiratory Medicine and Potential Role in Asthma and COPD Diagnosis

Developing an ML pipeline for asthma and COPD: The case of a Dutch primary care service

The Beginning of a New Era: Artificial Intelligence in Healthcare

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