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Impact of AI into Medical Science- Ambiguous
Impact of AI into Medical Science

Impact of AI into Medical Science

Shrikant Srivastava
Ankit Singh | October 25, 2019

Impact of AI into Medical Science is predicted to decrease medical costs as there will be more accuracy in diagnosis and better predictions in the treatment plan, as well as more prevention of disease, The future of medical practice, with AI,  is coming soon. Because of many advances in artificial intelligence data generated in clinics and stored in electronic medical records. These applications of artificial intelligence to change and will continue to change the way both doctors and researchers approach clinical problem-solving.

Impact of AI into Medical Science

AI can do many of those things that humans do, but it is done more efficiently, quickly and at a lower cost. The potential for both AI and robotics in healthcare is increasing day by day. AI and robotics are being a part of our healthcare Eco-system. The Need for AI in Healthcare is that It puts consumers in control of health and well-being. Additionally, AI increases the ability of healthcare professionals to better understand the day-to-day patterns and needs of the people they care for, and with that understanding, they are able to provide better feedback, guidance, and support for staying healthy.

Benefits of AI in Healthcare:

  • Advancement in treatments:

AI is always leading to advancements in healthcare treatments, as it helps in improving the organization of treatment plans, analyzing data in order to provide better treatment plans, and monitoring treatments.

AI has the ability to more accurately and quickly identify signs of disease in medical images, like MRI, CT scans, ultrasound, and x-rays, and it allows faster diagnostics by reducing the waiting time of the patients for a diagnosis. Artificial intelligence also helps in speed up the introduction of treatment options.

  • Virtual Assistants:

Nowadays when people expect to get answers instantly, the virtual assistant helps patients to get answers in real-time. Patients can ask medical questions to the virtual assistance and receive answers; they can get more information and reminders about taking medications, information about reports to physicians, and gain other medical support. Physicians can also take advantage of virtual assistants by tracking and making sure they are ordering the correct medication for patients.

  • Reduce Costs:

According to one report, Artificial intelligence has the potential to improve outcomes by 30- 40% and it can reduce the cost of treatment by 50%. It helps in improvements in efficiency that means it leads to fewer human errors, leading to a decrease in doctor visits. Doctors are able to get information from data of patients who are at risk of any certain diseases so that they can prevent hospital re-admissions.

Impact of AI in medical science

These are some points to look at the impact of AI in medical science 

  • Keep a healthy lifestyle:

One of AI’s benefits is to help people stay healthy so they don’t need to visit the doctor, or at least not as often. Consumer health applications use AI and the Internet of Medical Things (IoMT) is already helping people. Many technology applications encourage healthier behavior in individuals and help them to get a healthy lifestyle.

AI increases the ability of healthcare professionals to better understand the day-to-day needs of the people, and with the help of that understanding, they are able to provide better feedback, guidance, and support for staying healthy.

  • Early-stage disease detection:

AI is used to detect diseases such as cancer, and It can get more accurately in its early stages. According to the American Cancer Society, 1 in 2 healthy women being told they have cancer. The use of AI is enabling review and translation of mammograms (detection of breast cancer) 30 times faster with 99% accuracy which is reducing the need for unnecessary biopsies.

The increase of consumer wearable and other medical devices is combined with AI which is also being adapted to look at early-stage heart disease. It also enables doctors to better monitor and detects disease at earlier and in more treatable stages.

  • Diagnosis of disease:

IBM’s Watson is helping healthcare organizations apply cognitive technology to unlock large amounts of health data and power diagnosis.  Watson can review and store more medical information such as medical journals, symptoms, and case studies of treatment and response of the patients around the world, faster than any human.

Google’s DeepMind Health is also working in partnership with clinicians, researchers, and patients so that they can solve real-world healthcare problems. The technology they are using is a combination of machine learning and systems neuroscience so that they can build powerful learning algorithms that can act like the human brain.

  • Decision making:

In order to improve health, it requires the alignment of big health data with appropriate and timely decisions, and predictive analytics so that it can support clinical decision-making and actions.

AI uses pattern recognition to identify the patient’s condition and see their decline in health due to lifestyle, environmental, genomic, or other factors.

  • Patient treatment:

Scanning health records help providers to identify ill individuals, AI can help clinicians take a step ahead for disease management, better coordinate care plans. AI also helps patients to manage and comply with their long-term treatment programs.

Robots have been used in medicine for many years. There is a range from simple laboratory robots to highly complex surgical robots that can either assist a human surgeon or execute operations by themselves. The robots are also used in hospitals and labs for repetitive tasks, physical therapy, etc.

  • Lifecare:

As we approach the end of life, we are dying in a different and slower way such as from conditions like dementia, heart failure, and osteoporosis.

Robots have the potential to help people to remain independent for longer, it is also reducing the need for doctors to visit in-home regularly. AI is combined with the advancements in the humanoid design, it is enabling robots to have ‘conversations’ and other social interactions with people to keep aging minds sharp.

  •  Research:

The path goes to the research lab to the patient is a costly one. According to the California Biomedical Research Association, it takes an approximate 12 years for a medicine to travel from the research lab to the patient. Only five in 5,000 of the medicine that begins pre-clinical testing which makes for human testing and just one medicine out of these five medicines is ever approved for human usage. It will cost the US $359 million to a company to develop a new medicine from the research lab to the patient.

Medicine research and discovery is a recent application for AI in healthcare. The latest advances in AI to organize the medicine discovery. AI has the potential to significantly cut time and cost to market for medicines.

Conclusion: Impact of AI into Medical Science

It is a possibility that AI has a huge and positive impact on doctors and patients in healthcare. Because of this ability to analyze a large amount of varied data, AI can provide faster and more accurate diagnoses for patients. Individuals who do not have access to highly specialized healthcare can also take the benefit of that experience with the help of AI. The cost of healthcare could drop due to earlier and more accurate diagnoses. Artificial intelligence also has some risks for the medical profession and patients, until the data gets well validated. Doctors will have to use their training and experience to assure that artificial intelligence is providing the proper diagnoses and medical treatment. There is a risk that Artificial intelligence can learn incorrectly if it is just presented with a large amount of data that has not collected carefully. If a wrong diagnosis is done then it can risk into patient life so it is important that Artificial intelligence offers exceptional accuracy in many focused tasks. It can be done by the existing judgment and training of clinical experts.

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