The Top 10 Ways AI Is Helping Women to Focus on Their Bodies

Top 10 ways AI is helping women

The top 10 ways AI is helping women focus on health and body

Medical researchers and makers of medical equipment are transforming their approaches to healthcare of women as a result of AI’s impact on healthcare. The AI technology is speeding up current procedures and AI for women’s health is opening the door to some novel healthcare ideas. Here are 10 applications of AI for women’s health and wellbeing.

1. Providing Clinical Support

There is a lot of medical literature available that clinicians with the time can use to guide treatment. Doctors, on the other hand, rarely have this chance, which may limit their capacity to treat patients with uncommon illnesses. For instance, dermatological patients may have complicated medical histories that lead to a variety of symptoms. Careful management of the treatment for these symptoms is necessary.

2. Drug Repurposing

It is challenging to develop new medications. A medicine typically needs to be developed for more than ten years and cost $2 billion before receiving federal approval. As a result, many pharmaceutical firms concentrate their R&D efforts on finding new uses for currently authorised medications. An AI programme can efficiently find candidates for drug repurposing by contrasting the composition and outcomes of unused medications with those of already available treatments.

3. Virtual Nurses

Hospitals frequently experience a variety of severe challenges, including time and financial ones. As a result, patients may occasionally be kept in the dark regarding their condition because the care members surrounding them are too busy to provide detailed information. MedTech businesses are developing virtual AI nurses that can offer round-the-clock bedside assistance.

4. Developing New Vaccines

Adjuvants, which are substances that aid the immune system in fighting disease, are included in several contemporary flu vaccines. These vaccinations could become even more beneficial through the discovery of novel adjuvants. It takes a long time, though, just as finding new drugs. Also, in this case, AI is helpful. Australian researchers employed AI to do analysis.

5. Extracting Data from Medical Records

A patient’s medical history and treatment plans are covered in electronic health records (EHRs), which are lengthy and frequently cumbersome documents. While these EHRs have benefits over handwritten notes, they are notoriously slow to look through. Important information, such as a history of blood tests and allergies, could thus be overlooked.

6. Improving Pathology

Despite the fact that pathology has been around for 150 years, little has changed in the techniques used to diagnose cancer. Clinical pathologists still devote a significant amount of their time to studying tissue samples that don’t provide any valuable data. This analysis procedure can be greatly accelerated by AI.

7. Screening for Lung Cancer

A CT scan of the patient’s lungs is necessary as part of the standard screening procedure for lung cancer. Although this scanning technique is efficient, it is time-consuming and exposes patients to dangerous radiation levels. Researchers recently created an AI that can expedite the scanning process and clean up the scan findings.

8. Uncovering Other Types of Cancer

Other cancer kinds are also being treated with similar technology. One recent AI, for instance, showed to be more accurate than radiologists at spotting breast cancer symptoms in mammograms. This technology will soon be able to speed up diagnosis, increase accuracy, and free up doctors’ time.

9. Screening for Complications Related to Diabetes

The most common cause of adult blindness in America is diabetic retinopathy, which is also a consequence of diabetes. However, if the illness is identified early on, it can be managed and even cured with minor dietary adjustments. The AI-powered screening tool IDx-DR has received FDA approval and can detect diabetic retinopathy.

10. Predicting Adverse Reactions to Drugs

Injuries brought on by or connected to pharmaceutical use are known as adverse drug events (ADEs). When analysing a patient’s medical history, hospital staff should typically be able to identify any potential ADEs, but mistakes may occur. Hospitals incur an estimated $4 billion in annual costs as a result of ADEs, which often cause hospital stays to be extended by two to three days. With the help of cutting-edge AI technology, a treatment plan may be automatically flagged if it may clash with a medication a patient is taking or with some component of their medical history.

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