Artificial intelligence has immense scope in the medical field. There is a greater need for AI more than before inpatient treatment and care. There is tremendous growth for AI in the health sector and is continuing to emerge rapidly in a few decades.
Let’s view below the tasks that make use of AI in medical science:
- Gathering patient’s history through interviews and tests.
- The data is processed and analyzed thoroughly.
- Accurate diagnosis of the patient’s clinical condition using various data sources.
- Determining the proper treatment required.
- Upgrading medical equipment to save time and to make operation process advance.
- Preparation and providing the treatment.
- Careful monitoring of the patient.
- Aftercare procedures and following up of appointments.
- For professionals:
- The primary advantage of using AI is it keeps the professional’s time, and a lot of tasks are completed quickly.
- It is also useful in the development of drugs, treatment personalization, and gene alterations.
- For hospitals:
- Easy payment selections
- Reduced waiting period
- Fewer or zero errors since it is automated
- Patient satisfaction
Let us check the various steps in a clinical trial and assessment of a patient below:
AI conducts a proper diagnosis of diseases with the help of algorithms. It has surpassed radiologists in the detection of tumors. Many methods are applied in the medical field. It gives a qualitative evaluation of radiographic data. It has an excellent future in the field of oncology.
The other fields that depend on AI include pathology, ophthalmology, genetics, dermatology and psychiatry. It also has uses in maintaining electronic health records.
After diagnosis, the next step is characterizing the extent of the disease. Features like the size of the tumor, its stage, internal texture need to be identified. AI can detect even minor differences in the CT scan. It makes use of biomarkers.
Biomarkers use digital tools to collect data and converts them into meaningful data and provides immediate feedback or report to the patients or the medical team. AI can analyze large amounts of data generated.
- Treatment Applications:
AI has achieved success in providing proper treatment protocols for patients. It supports clinicians in making decisions. For example, cancer is inherited, and hence humans are unable to detect all variants and their response to medicines. In this scenario, AI pitches in.
- Patient monitoring:
Chatbots can play a vital role in monitoring the patient’s health status after treatment. They remind patients to take medicines on time to avoid any complications. They can converse with patients like humans and spare the time for medical staff to attend to more severe cases.
- Aftercare procedures and appointments follow-up:
AI helps in appointment scheduling. The patient’s time is fixed in the given time slot. There are so many cases where a patient’s appointment is canceled or delayed. In those cases, AI helps in rescheduling and fixing newer appointments. It helps in the optimal use of hospital human resources and time.
AI inpatient care is quite cost-effective and improves a patient’s overall health. It can layout health care plans. Many apps help surgeons to implement recovery programs and make it available to their patients.
AI is yet to achieve many more milestones in the medical industry. A proper understanding of the technologies must be encompassed to the medical staff for the active development of the hospital workspace.