Machine learning and artificial intelligence research for patient benefits

Healthcare organizations have only one core target -- to provide the best of the healthcare and treatments for their clients. Thus, it can be said patient benefit is the pillar that it stands on. However, with the rising number of patients, the need for technological advancements and more sophisticated treatment patterns is making the process quite difficult to be handled with efficiency of time and cost. As a result, current technologies like machine learning (ML) and artificial intelligence (AI) are used for the benefit of patients.

With the rising impact of ML and AI in other industries, it is quite clear that having the right tools to understand the data and integrate it with other processes of the healthcare organizations is of paramount importance. The potential of making processes more feasible and efficient using these technologies is immense and profound.

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Diagnosis of the ailments and patient care

One of the most useful means of using ML and AI is in the diagnosis of the ailments at the early stage. Herein, the data all across the cyberspace can be used to identify the early symptoms of the patients. This process can help in identifying the problems in time and also make sure that the right treatment is provided before the situation worsens. Medical data from digital files, journals, case studies, and treatment profiles are all useful in obtaining a better diagnosis. Machine learning and neural networks are used to build algorithms that can identify and predict the disease in real time.

Devices like wearables along with other health care devices can be utilized to monitor the symptoms and can provide a diagnosis that is more up-to-date and treatable. These devices can help in monitoring various statistics like blood pressure, heart rate and temperature. This information can be very insightful for the doctors, as they can keep a check on the patients and their symptoms in real time. AI is also revolutionizing the process of end of life care, in which it is trying to keep the patients with terminal illness self-dependent.

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Treatment coordination and decision making

Healthcare facilities tend to treat thousands of patients daily and most of the institutions tend to have a chain of branches spread across the country, which may make treatment coordination quite a difficult task. Whether it is for medical program compliance or to track the medical policy benefits, there is a lot of coordination that is required among the various institutions. This can be simplified by using ML and AI, which can help in disease management and coordinating patient care.

AI and ML algorithms can also help in taking timely decisions with complete data alignment and integration. ML helps in predictive analytics and pattern recognition that can assist in the prioritization of tasks and in taking timely clinical decisions.

Genetic and drug research

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To treat new diseases and also deal with more sophisticated genetic disorders, medical researchers and doctors need to continue their research work. Researching and creating a drug is a long process and at times can take up to 10 to 12 years. However, with AI and ML, it has become a real possibility to test and research drugs in a shorter period of time. AI also helps in repurposing the drugs and streamlining various drug discoveries.

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