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Appliance of Machine Learning Algorithms in Prudent Clinical Decision-Making Systems in the Healthcare Industry
| Content Provider | Scilit |
|---|---|
| Author | Rao, T. Venkat Narayana Akhila, G. |
| Copyright Year | 2020 |
| Description | Book Name: Soft Computing Applications and Techniques in Healthcare |
| Abstract | The most significant and fastest growing field of study in the present era is machine learning (ML) and artificial intelligence (AI). ML and AI technologies have impacted all spheres of healthcare industries/services, from improving healthcare supervision to innovative drug discovery expertise. Although computers cannot wholly replace doctors and nurses, current technologies are already revolutionising the healthcare business to a new level of excellence and assistance in the medical practices. Many software companies are now offering machine learning algorithms and predictive analytics to advance the efficiency of the drug discovery procedure, offer support to patients and analyse diseases by processing medical images. The value of machine learning in healthcare is its capability to process enormous datasets far from the scope of human ability, and then consistently translate analysis of data into medical insight that assists physicians in the preparation and offering of care, eventually leading to better outcomes, low cost care and enhanced patient satisfaction. Machine learning can be trained to study images, recognise abnormalities and spot the areas that require awareness in order to improve the precision of all processes. Machine learning helps medical practitioners obtain opinions to improve competence, trustworthiness and accuracy. The studies have found that machine learning promises unlimited improvement and speeds up clinical workflow with less financial burden. The usage of modern technology and predictive algorithms offer diminish readmissions and avert hospital-acquired infections. The drug discovery/manufacturing reduces hospital length of stay, predicts propensity to pay, predicts chronic disease, creates accurate predictive models and makes available clinical trial research followed by epidemic outbreak prediction. The chapter proposes a description on how predictive insight through machine learning can be developed that offers better models of mortality that doctors can employ for a timely, accurate decisions in order to administer better treatments. |
| Related Links | https://content.taylorfrancis.com/books/download?dac=C2019-0-07443-2&isbn=9781003003496&doi=10.1201/9781003003496-9&format=pdf |
| Ending Page | 184 |
| Page Count | 22 |
| Starting Page | 163 |
| DOI | 10.1201/9781003003496-9 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2020-09-09 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Soft Computing Applications and Techniques in Healthcare Decision Making Healthcare Treatments Machine Learning Algorithms Doctors Predictive Algorithms |
| Content Type | Text |
| Resource Type | Chapter |
