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5 Uses of AI in the Healthcare Industry

In this information and technology-driven era, a wide range of intelligent technologies, such as Artificial Intelligence, have succeeded to enter several industries.

The healthcare industry is no exception in this case.

Over the last few years, it has witnessed the increasing incorporation of AI. According to a CB Insights report, Artificial Intelligence is used by 86 percent of life science organisations, healthcare providers, and technology vendors. In addition, other industries that are directly or indirectly tied to healthcare are evolving, and AI and automation are to blame. According to the same estimate, healthcare organisations will spend an average of $54 million on various AI projects.

Artificial intelligence (AI) has a lot of promise when it comes to human health, especially when it comes to life and death situations. While there is still much to overcome in order to achieve AI-assisted health care, most notably data privacy concerns and fears of mismanaged care due to machine error and a lack of human oversight, there is enough potential that governments, tech companies, and healthcare providers are willing to invest in and test AI-powered tools and solutions. 

Traditional analytics and clinical decision-making tools provide a lot of advantages that AI does not. As humans engage with training data, learning algorithms can become more exact and accurate, allowing humans to obtain unparalleled insights into diagnosis, care processes, treatment variability, and patient outcomes.

Let's look at how AI is being used in healthcare mobile app development and how it could alter the sector.

AI-Assisted Robotic Surgery

With an estimated value of $40 billion to healthcare, robots may evaluate data from pre-op medical records to direct a surgeon's tool during surgery, which can result in a 21% reduction in a patient's hospital stay, according to estimates. Because robot-assisted surgery is "minimally invasive," patients will not need to recover from huge incisions. Robots can use data from previous procedures to inform future surgical approaches thanks to artificial intelligence. The excellent outcomes are really encouraging. When compared to surgeons working alone, AI-assisted robotic treatments resulted in five times fewer problems, according to a study involving 379 orthopaedic patients.

Virtual Nursing Assistants

Technology impact on home healthcare is really taking over the market with innovative ideas for mobile apps. Virtual nursing assistants might save the healthcare industry $20 billion per year by communicating with patients and sending them to the most appropriate care environment. Virtual nurses can answer inquiries, monitor patients, and give timely responses because they are available 24 hours a day, seven days a week. Most virtual nurse assistant applications currently allow for more frequent communication between patients and care providers between office visits, reducing the likelihood of hospital readmission or unnecessary hospital visits. Care Angel's virtual nurse assistant can even do wellness checks using voice and artificial intelligence.

Image Analysis

Image processing takes a long time for humans, but an MIT-led research team devised a machine-learning method that can analyse 3D images 1,000 times faster than is now achievable. This near-real-time examination can provide crucial information to operating surgeons. It's also envisioned that AI would aid in the development of future imaging instruments that don't require tissue samples. Furthermore, AI picture analysis could help remote places with limited access to healthcare providers and even improve telemedicine by allowing patients to send in photos of rashes, scrapes, or bruises to determine what treatment is required.

Building Intelligence into Medical Devices

The medical device sector will be catapulted into the twenty-first century by the convergence of technology impact on home healthcare, robots, and machine learning algorithms. Because biofeedback signals such as blood pressure, heart rate, and blood plasma levels of dissolved gases and pharmaceutical medications are constantly monitored and adjusted, devices such as ventilators and anesthesiology machines will be attractive candidates for automation.

Time-series data is a term used to describe this type of information. Humans find it difficult to examine data efficiently, but artificial intelligence machines can be trained to spot anomalies and crunch this type of data to accurately forecast health issues.

Clinical Decision Making

The use of artificial intelligence (AI) in healthcare mobile app development can cut down on the time and resources required to assess and diagnose patients. Medical workers can save more lives by acting faster as a result of this. Traditional procedures cannot identify danger as quickly or accurately as machine learning (ML) algorithms can. These algorithms, when used effectively, can automate inefficient, manual operations, speeding up diagnosis and lowering diagnostic errors, which continue to be the leading cause of medical malpractice lawsuits.

AI-enabled technologies can assemble and filter through enormous amounts of clinical data to give clinicians a more holistic perspective of patient groups' health. These technologies provide the care team with real-time or near-real-time actionable information at the proper time and location to improve care outcomes dramatically.

Conclusion

The rapidly growing volume of patient data both within and outside of hospitals shows no signs of slowing down. Healthcare organisations are under pressure from ongoing financial challenges, operational inefficiencies, a global shortage of health workers, and rising costs. They need technology solutions that drive process improvement and better care delivery while meeting critical operational and clinical metrics.

In the highly complicated realm of healthcare mobile app development, AI tools can assist human practitioners in providing speedier service, diagnosing problems, and analysing data to detect trends or genetic information that may predispose someone to a specific disease. AI and machine learning can be transformative not only for healthcare but for every single patient when saving minutes can mean saving lives.

In case you are looking to scale up by integrating AI, get in touch with an experienced healthcare mobile app development company.

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