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AI Revolutionizing Healthcare: A New Era of Medical Advancements

In this post:

  • The use of AI in the healthcare industry is creating room for novel solutions that improve care for patients and clinical workflows. 
  • Advancements in AI-based technologies have proved to be quite prospective for the improvement of diagnosis accuracy.
  • According to the World Economic Forum, the healthcare AI market will reach $188 billion by 2030. 

Artificial intelligence (AI) is revolutionizing the healthcare industry and is expected to answer longstanding challenges in patient care. Starting from error reduction and ending with rebuilding trust between patients and medical practitioners, the AI is ready to deliver a new phase of medical achievements. Advancements in AI-based technologies have proved to be quite prospective for improving diagnosis accuracy, optimizing workflows, and ensuring patients’ success.

Wearable devices and AI algorithms

The use of AI in the healthcare industry is creating room for novel solutions that improve care for patients and clinical workflows. The wearable devices using AI algorithms, like Apple’s forthcoming health coach and mood tracker, are leveraging data from smartwatches to provide personalized health suggestions and workout areas. Also, Internet of Medical Things (IoMT) devices, which use advanced AI, provide remote monitoring features to find early signs of problems and enhance patient outcomes.

The wearable devices and mobile apps enable healthcare providers to remotely monitor in real-time patients’ health-related metrics, which improves patient engagement and compliance and facilitates timely interventions. AI-based recognition technology can also automatically record health data.

According to the World Economic Forum, the healthcare AI market will reach $188 billion by 2030. In the same year, it’s estimated that we will be missing approximately 10 million physicians, nurses, and midwives as the population becomes older and requires more healthcare

The promise of AI in disease diagnosis

AI algorithms and deep learning are demonstrating promising chances in a number of healthcare fields. Research by the Government Accounting Office demonstrated that a number of machine learning (ML) technologies can diagnose diseases in an early stage and deliver consistent analysis of medical data.

For instance, FPT Software applied AI predictive analytics in detecting pneumothorax and kidney tumors. These winning solutions have been recognized at two healthcare technology competitions: the Pneumothorax and the KiTS-2019 Grand-challenge.

Another study has found that AI can initiate radiology imaging follow-up to prevent delayed and missed care. Early identification of disease, more effective addressing of diagnostic errors, and reducing delays are keys to better patient outcomes and lower healthcare costs.

Similarly, researchers are coming closer to the possible utilization of smart contact lenses which are able to monitor blood glucose levels as a tool for detecting and managing diabetes. Ten years ago the initiative was jointly launched by Google and Novartis but a research paper published a month ago by Yonsei University, Republic of Korea has shown actual improvement in animal and human trial of the technology.

Addressing challenges and the way forward

Although the future of AI in healthcare looks bright, challenges remain. The implications of predictive models on treatment choices and the necessity of continuous teaching of algorithms are among the issues which reflect the difficulty of implementing AI in medical practice.

Institutional cooperation and the creation of ethical AI policies are crucial to deal with these challenges in the right way. In addition, as the regulatory systems change worldwide, healthcare organizations have to alter in order to remain compliant and to protect patient safety. 

We are still scratching the surface of penetrating AI into the global healthcare systems. But, the indications are that we stand at the threshold of something huge when it comes to AI-enhanced prognoses, preventive medicine, and treatments. However most observers emphasize that what is actually required is to provide the professionals with the means of enhancing outcomes rather than to overthrow the whole system.

Disclaimer. The information provided is not trading advice. Cryptopolitan.com holds no liability for any investments made based on the information provided on this page. We strongly recommend independent research and/or consultation with a qualified professional before making any investment decisions.

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