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Advancing Healthcare Delivery via Artificial Intelligence

Advancing Healthcare Delivery via Artificial Intelligence

Technology and the evolution of the medical industry go hand in hand. As we are getting better machines to analyze, manufacture, and distribute the medicines, we are getting better at the quality and effects of medicines too.

Artificial Intelligence has improved the medical industry with the help of the ability to contact, communicate, and potency to solve highly complicated algorithms. Furthermore, AI has also simplified the tasks that earlier humans felt to be time taking and difficult.

Concerning the healthcare industry, AI has shown a lot of success in a variety of aspects. Studies say that AI integration has helped pharmaceutical companies and research institutions to improve their productivity. In fact, these AI-based machines are often found to outperform the radiologists assigned for the same work.

Let us learn more how advanced technology- Artificial Intelligence boosted the pharmaceutical companies and the healthcare industry.

Applications of AI in Healthcare

AI in Healthcare caters to three categories- patient Oriented AI, Clinician Oriented AI, and Administrative and Operational Oriented AI.

The application of AI makes tasks from complex to easy. Everything from answering the phone calls of medical record review to population health trends, to reading radiology images, to therapeutic drug design, to clinical diagnosis to treatment plants to even interacting with the patients- everything is easy.

Drug Discovery

Drug Discovery

Earlier, the medicines were discovered with the aspect of considering their benefits and rigorous studies and experiments for years. Only then, it was termed to be beneficial for human use. However, with the advancing machines, you can easily examine and make the experimentation process quicker and easier. Thus, this helps in improving the old drugs in the market as well as come up with new ones quicker.

Drug manufacturing

Drug manufacturing is another aspect that involves AI integration to help the healthcare industry, specifically the pharmaceutical companies to make the manufacturing process better. The traditional methods of drug discovery and hence the manufacture were more prone or susceptible to meet failures. However, with AI integration in the companies, manufacturing has eased up.

Drug Marketing

After drug manufacturing comes drug marketing. The introduction of AI in marketing provides a broader scope of platforms for the companies to work upon the selling techniques. Procure data and analyze the large volumes of them for a better drug in the market in the most efficient manner. Further, it helps in wide-spreading the medicines in the world without a lot many barriers.

Clinical Trials

Clinical Trials

Clinical Trials have become easier. Earlier, in the case of conventional methods, the clinical trials had a probability to fail. However, now one can use AI-based machines to optimize the safety and potency of the drugs. One can understand the true potential of the drugs via AI-based solutions in the process.

Diagnosis Treatments

Moreover, the other sector of the healthcare industry that has seen a drastic improvement is “The diagnosis and the treatments”. The old school methods involved the doctor’s experience and expertise to diagnose the problem in the patients. On the other hand, Artificial intelligence machines have also made the treatments better and thus increased the mortality rate.

Implementing AI in Healthcare: Lessons learned

  • Even the small-scale pharmaceuticals or clinics get more time and better quality in their hands.
  • More savings by cutting the costs and taking advantage of the open-source technologies with limitations in the customization.
  • Involve only those with a sound knowledge of technology and healthcare, who have a better understanding of meeting the consumer’s needs.
  • Carefully work on the data to train with the right AI model that trains about the production data and does not become a bias model.
  • Training of Models is an ongoing process, and it can take time. Thus, the expected ROI on the same should be well calculated to fit within the time frame.

It is high time for the healthcare industries to prepare and buckle up with the Artificial Intelligence integration in their services. Once you take the process and governance, financial aspects, organizational and cultural aspects under consideration, you can prepare yourself with these new technologies.


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