14 Real World Applications of Artificial Intelligence (AI) in the Healthcare Industry

The spread of new technologies in the information age has upended many sectors. The same applies to health care. Automation, machine learning, and artificial intelligence (AI) have been affected by automation, machine learning and artificial intelligence (AI), often and significantly more positively than other sectors. Approximately 86% of healthcare related organizations use AI technologies. These companies will invest an average of $54 million in AI initiatives in the coming years.

So what solutions do they use frequently? Here are 14 ways AI is already impacting and will continue to change healthcare.

  1. Robot-assisted surgeries

Robotic surgery speeds up and improves the accuracy of surgical procedures. Many people fear the use of surgical robots in healthcare because they believe that AI-powered robots can decide how an operation should be performed. Robotic technology assists surgeons with more precise and precise surgical movements; The process is still under the supervision of a person. For example, the Mayo Clinic in Florida is using artificial intelligence-powered robots to help perform abdominal procedures and is currently developing more for brain surgery.

  1. fraud detection

Many countries make health care claims to their citizens to enable them to obtain medical care even when they cannot pay the high price. However, medical claims can be submitted fraudulently, resulting in annual losses of hundreds of dollars. AI is also working on this issue. Through automatic assessment of claims from AI, fraud can be prevented. Machine learning models powered by AI can quickly assess, approve and pay valid claims by identifying invalid claims. In addition to these insurance claims, AI assists with additional fraud detections. It can detect unpaid bills of patients and protect their personal information from theft.

  1. Medical data and records management

Data management is the most widely used application of artificial intelligence and digital automation, as the first step in healthcare provision is the collection and evaluation of information (such as medical records and other historical data). Bots collect, archive, reformat, and track data to enable faster and more reliable access.

  1. treatment plan

Artificial intelligence systems were developed to evaluate data, including notes and reports from patient files, external research, and clinical experience, to help select the best and most personalized course of treatment.

  1. Online counseling

Using artificial intelligence, apps like Babylon in the UK provide medical advice based on the user’s medical history and accepted medical practices. Users enter their symptoms through the app, which compares them to a database of diseases using speech recognition. Babylon then presents a suggested course of action taking into account the user’s medical history.

  1. Online Nursing Assistants

AI systems mitigate the need for on-demand virtual nursing assistants. Virtual nursing assistants could help the healthcare industry save $20 billion annually by connecting with patients and sending them to the most appropriate place of care. They can monitor patients, respond to their inquiries, and provide immediate immediate responses. Most virtual nursing assistant apps available today allow patients and healthcare professionals to communicate frequently and consistently. There is less risk of unnecessary hospital trips or readmissions because this occurs between patients’ visits to their doctors’ offices. In addition to scheduling doctor visits and tracking patients’ health, AI-powered virtual assistants provide individualized experiences to patients and help them identify their illnesses based on their symptoms.

  1. Acknowledging prescription errors

Poor electronic health record (EHR) interfaces often cause errors that confuse clinicians, causing them to incorrectly select incorrect medications from dropdown options or dosage units. However, ML models may analyze EHR data using artificial intelligence and compare new prescriptions for each patient. Doctors can evaluate and correct specific treatments that do not follow expected trends. Consider Brigham and Women’s Hospital, which uses AI-powered software to identify and correct prescription problems.

  1. medication management

People with serious medical conditions, patients who frequently ignore medical advice, and participants in clinical studies may be the most common users. The National Institutes of Health developed the AiCure app to track a patient’s medication use. Artificial intelligence and a smartphone webcam automatically checks that patients are taking their medication and helps them manage their illnesses.

  1. Drug discovery and development

Clinical experimental drug development can take more than ten years and cost billions of dollars. The world could change if this process was done faster and more affordable. In the midst of the recent Ebola virus crisis, an AI-powered tool was used to evaluate existing drugs that could be altered to treat the disease.

  1. health monitoring

Heart rate and activity levels are tracked by wearable health trackers such as those made by FitBit, Apple, Garmin, and other companies. They can share this information with clinicians (and AI systems) to obtain additional data points about patient requirements and behaviors, as well as alert the user to perform more exercises.

  1. health care system analysis

In the Netherlands, 97% of medical bills are electronic. A Dutch startup is using artificial intelligence to filter data, identify inefficient workflows, treatment errors, and hospital admissions that may have been avoided.

  1. Administrative workflow assistance

The healthcare sector could save about $18 billion due to AI applications. One of the uses of AI in healthcare is to automate administrative workflow. It ensures that healthcare professionals prioritize important work, allowing doctors, assistants and nurses to spend less time on routine tasks. The administrative side of healthcare can make use of technology such as voice-to-text conversion. They help automate non-patient care tasks such as ordering tests, recommending drugs, and creating chart notes. Artificial intelligence in healthcare includes a collaboration between IBM and the Cleveland Clinic. IBM’s Watson analyzes large amounts of data to help clinicians provide their patients with highly effective and customized care. Additionally, medical professionals can use natural language processing to analyze thousands of medical papers (NLP).

  1. Provide individualized care

Medications and treatment regimens have varying effects on different patients. The potential to extend patients’ lives is enormous with individual treatment options. Personalized care is delivered through machine learning. How? It can help identify features that indicate a patient will react in a certain way to a particular course of treatment. It can predict how likely a patient will respond to a particular treatment. How does the ML algorithm detect this? The system gains this knowledge by comparing similar treatments and patient data outcomes. This helps doctors create the best possible treatment plan for the patient.

  1. Improving Gene Editing

In addition, genomic research uses artificial intelligence. Machine learning methods are increasingly being integrated into other fields, including genomic annotation and sequencing. In addition, it is used by genome-based diagnostics. Significant progress has been made in our ability to precisely and inexpensively modify DNA thanks to CRISPR, particularly the CRISPR-Cas9 gene-editing system.

By incorporating more robotic technologies and virtual support that improve the effectiveness of care delivery, AI-powered technology is revolutionizing healthcare. It enables clinicians to quickly create effective treatment programs for patients and early detection of infectious diseases. These are just a few of the options that AI provides to the healthcare sector. There will be additional opportunities to save time, reduce costs and improve accuracy as innovation drives automation capabilities and the digital workforce.

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References:

  • https://www.novatiosolutions.com/10-common-applications-artustry-intelligence-healthcare/
  • https://www.healthcareitnews.com/news/86-healthcare-companies-use-some-form-ai
  • https://digitalhealth.folio3.com/blog/example-of-artuable-intelligence-in-healthcare/
  • https://imaginovation.net/blog/5-real-world-applications-ai-in-medicine-examples/
  • https://www.compunneldigital.com/blog/ai-in-healthcare-top-5-real-world-examples/


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