Machine Learning is the Panacea for Patients

Machine Learning is the Panacea for Patients

Machine learning in patient care is a combination of medicines and machines, which helps to improve a patient’s overall health, including accurate diagnosis and better treatment plans.

Machine learning is about understanding data and statistics, where computer programs find patterns in data, which results in predictable outcomes. Machine learning enables computer systems to adapt to changes on its own without being programmed explicitly. For instance, your email program can scan messages you receive through links, words in the subject line, etc. and identify dubious messages as SPAM. Machine learning quickly adopts new patterns and correctly identify a SPAM message if spammers change their tactics. Machine learning has its hands in numerous areas ranging from banking, insurance, fraud prevention, plagiarism checker, etc. and now also helping the healthcare industry. “Using a weighted average of the 4 studies, a lower limit of 210,000 deaths per year was associated with preventable harm in hospitals.” This states the number of people who die due to incorrect medical diagnosis and treatments. Machine learning in patient care will significantly resolve these issues, where machines can be used to interpret data better than the human mind.



Benefits offered by Machine Learning

One of the exciting benefits of machine learning is that systems will eventually learn and adapt new environment for the given present task, which was once trained on entirely different datasets. Machine learning enables marketers to understand customer’s behavior and accordingly send them best possible offers based on their browsing and purchase history. Machine learning provides predictive maintenance, which helps companies to discover insights and hidden patterns in the company which helps to reduce risks associated with failures and enhanced costs. Machine learning, along with other modeling algorithms can eliminate errors caused during manual data entry. This allows employees to utilize their time to add productivity to their company. Machine learning helps overcome cyber threatsand many other unknown risks associated with space exploration. Machine learning helps improve customer relationship based on the behavior of customers, using predictive analysis.

Machine Learning in Patient Care

The concept of machine learning in patient care is not so much about replacing doctors with robots as it is about enhancing a doctor’s expertise. Machine learning techniques can be useful in the diagnosis and treatment of dreadful diseases like cancer. Machine learning enables systems to incorporate a patient’s health details, such as details on the stage of a disease, and provide doctors to administer the right treatment. This helps doctors to analyze better treatment plans and help patients improve their health. It is difficult for doctors to provide the best treatment to all their patients with the limited amount of time allocated to each patient and then also to stay updated with all the latest advancements in the medical field. This can be done with the help of machine learning. Besides, machine learning helps doctors to treat their patient with confidence, thereby helping patients to improve at a faster pace. Machine learning is helping the medical field to identify mental disorders and to assist with mental healthcare as well. For instance, people suffering from depression will slowly reduce contact with their friends or family on social media and this behavior can be helpful for therapists to understand their patient well and treat them accordingly.

Machine learning in patient care compels us to think that it is not about ‘man against machine’, rather it’s the man with the machine, which can create remarkable improvements in the medical field.

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  • Angie Brown

    This article provided a useful lay-of-the-land of some of ML’s impact in the healthcare industry.

  • Martin Svendsen

    Deep learning will probably play a more and more important role in diagnostic applications as deep learning becomes more accessible, and as more data sources (including rich and varied forms of medical imagery) become part of the AI diagnostic process.

  • Charles Jones

    Scientists and patients alike can be optimistic that, as machine learning of pooled consumer data continues, researchers will have more ammunition for tackling tough diseases and unique cases.

  • Mark Collins

    While machine learning might help with “suggestions” in a diagnostic situation, a doctor’s judgement would be needed in order to factor for the specific context of the patient.

  • Anthony Gladue

    excellent read

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Naveen Joshi

Tech Expert

Naveen is the Founder and CEO of Allerin, a software solutions provider that delivers innovative and agile solutions that enable to automate, inspire and impress. He is a seasoned professional with more than 20 years of experience, with extensive experience in customizing open source products for cost optimizations of large scale IT deployment. He is currently working on Internet of Things solutions with Big Data Analytics. Naveen completed his programming qualifications in various Indian institutes.

   

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