Top 4 Investment Areas in the Generative AI in Healthcare Industry That Are Set to Transform the Medical Sector in 2024

28 May
2024

 
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Highlights:

  • Introduction
  • Role of generative AI in improving medical imaging
  • Contribution of generative AI in drug discovery and ensuring pandemic preparedness

 The healthcare sector has increasingly integrated emerging technologies over the past few decades. The digital revolution that was kickstarted with the advent of the Internet has further led to the adoption of different innovations and advancements. Many new forms of healthcare services that seek to improve outcomes at all levels of diagnosis, treatment, and rehabilitation have been launched in these years. Furthermore, the life sciences sector, too, has witnessed some stunning developments due to the use of technologies like Artificial Intelligence, machine learning, and data analytics. With the launch of the generative AI model, the healthcare sector is expected to further evolve in the coming period.

Automating administrative tasks and improving medical imaging capabilities with generative AI

At the most basic level, generative AI models are expected to help the healthcare industry in automating and simplifying administrative tasks in medical institutions. These models can provide technological support in terms of appointment scheduling, billing and claims processing, insurance verification, documentation and recordkeeping, and communication management. In March 2024, Nvidia, a leader in AI computing, announced the launch of Generative AI Microservices to improve the capabilities of digital health, drug discovery, and MedTech. Using these services, hospitals are now able to mitigate their staffing shortages and enhance the quality of patient-clinician interactions.

Another area where generative AI can play a crucial role in improving the overall outcomes is that of medical imaging. For instance, generative AI has been proven to be beneficial in enhancing the quality of medical images, by offering better visibility and thus aiding in accurate diagnosis and treatment of the disease. Also, studies have shown that the noise associated with medical images is substantially reduced with generative AI models. Furthermore, employing generative AI in healthcare imaging also enables medical practitioners to analyze different patterns in the patient’s reports, which ultimately aids in early detection and treatment.

Generative AI to enhance the drug discovery capabilities and risk prediction for pandemic preparedness

In December 2023, Merck, a leading science and technology company, announced the launch of its AIDDISON™ drug discovery software, a software-as-a-service platform designed to aid medical researchers in molecular design. This platform harnesses the power of generative AI, machine learning algorithms, and computer-aided drug discovery to accelerate the process of drug discovery. The launch of AIDDISON™ drug discovery software is considered by medical researchers as a ground-breaking innovation that will contribute to the growth of the generative AI in healthcare industry in the near future.

Such computer-aided drug discovery platforms have shown that generative AI can play a major role in analyzing biological datasets for identifying potential drug targets. This ultimately helps in predicting the efficacy of a drug and creating specific chemical compounds that work against a specific bacterium or a virus. Moreover, the use of generative AI in healthcare has also improved the capabilities of medical researchers to design personalized medicines using scientific approaches in genomics and proteomics. The repurposing of existing drugs to make them more effective against the diseases for which they have been designed has also been made possible with the help of generative AI.

Apart from drug discovery, generative AI has provided valuable support in the sphere of risk prediction to enhance the preparedness of medical facilities in case of the onset of a pandemic. The machine learning algorithms and natural language processing (NLP) models used by generative AI help it process huge volumes of data from a wide range of sources to recognize the patterns and early signs of emerging epidemics and pandemics. It can analyze different areas in a region based on parameters like environmental conditions, population density, health and sanitation measures, etc., to ascertain whether the said area could become the hotspot of the pandemic in the coming period. Finally, it can also aid in resource allocation to minimize the impact of the pandemic on overall community health.

To conclude, the incorporation of generative AI in healthcare and medical research activities has completely transformed the life science sector. By aiding in improving the medical imaging and drug discovery capabilities, diagnosis and treatment facilities in hospitals are expected to become much more advanced in the years to come. The support offered by AI and machine learning in terms of pandemic preparedness is expected to augment the growth rate of the industry exponentially.

 

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Akhilesh Prabhugaonkar

Akhilesh Prabhugaonkar

Author's Bio- Akhilesh Prabhugaonkar holds a bachelor’s degree in Electronics Engineering from the reputed Vishwakarma Institute of Technology. He has a special interest in the fields of forensics, world history, international relations and foreign policy, sports, agriculture, astronomy, security, and oceanography. An ardent bibliophile and melophile, Akhilesh loves to write on topics of his interest and various other societal issues. This love for writing made him enter the professional world of content writing and pursue his career in this direction.

 
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