Can AI take over the medical field?

Artificial Intelligence or AI is a fast-growing network in the world, constantly improvising and evolving according to the needs. AI attempts to mimic the capabilities of human intelligence. It can demonstrate higher cognitive processes like learning, reasoning, problem solving, planning and manipulation. AI has already slipped into our daily lives, in ways which we can’t avoid it. Virtual assistants like Amazon’s Alexa and Apple’s Siri, your Google suggestions are popular AI clouds.

One of the major fields AI is venturing into is the field of medicine, since in today’s world medicine also relies on large amounts of data. Ranging from early and accurate diagnosis to compatible treatment, AI has managed to help us in every way possible. Although, it does raise questions on data security and privacy invasion, since medical records and data are highly sensitive.

Here is a list of diseases that can be detected and monitored by AI.

A) Cancer

Researches from all over the world are working towards the detection, treatment and prevention of this deadly disease. Scientists are developing AI that helps to diagnose a wide range of cancer like breast cancer, skin cancer and lung cancer. An algorithm is developed using “deep learning”, which enables the computer system to imitate the brain’s neural networks.

Breast cancer

Scientists have been able to develop an AI that can detect breast cancer in women by screening the mammogram, decreasing the risk of wrong diagnosis and even predicting the cancer five years in advance. Highly trained radiologists are required to read the scans to diagnose and detect, even then some patterns in the tissues are hard to catch by the naked eye. Statistics have proved that AI is able to detect as accurately as any radiologist, sometimes even better diagnoses are provided by AI.

Lung Cancer

This cancer causes death to about 1.7 million people every year, and early detection of this category of cancer is difficult. But Google has recently developed an AI that, can detect lung cancer by analysing chest CT scans. The trained AI proved to be 5% more accurate when compared to the certified radiologist who did the same.

Skin Cancer

This area of research is still under process, but promises us favorable results. Scientistd are trying to modulate the deep-learning formula used in AI to identify the malignant melanomas and the identification of skin cancer. Dermatologist are surely going to benefit with the developments of the research.

B) Diabetic Retinopathy

Now AI can help you not go blind. Around the world about 400 million people have diabetes, and one third of them suffer from Diabetic Retinopathy that causes loss of vision. This AI can detect the symptoms that are missed out in most cases and can help save the sight of many!

C) Depression

Researchers have developed an AI to identify depression in children. Some of us might wonder, if little children suffer from depression? Well they do, and in their cases it is very hard to read the symptoms and catch the condition. The AI was able to identity speech patterns and detect depression with 80% accuracy. The speed and efficiency of the algorithm used impressed the researchers.

D) Genetic Disorders

You face is just not the index of your mind, it can also tell you if you have genetic syndromes.

FNDA, a biotechnology firm in Boston, developed an AI that can identify potential genetic disorders from scanning the photographs of people. Yaron Gurovich and his team developed the neural network called DeepGestalt. They have also launched an app Face2Gene powered by the algorithm, which is available on smartphones. The app is now working on the accuracy of identification of genetic syndromes in non-Caucasian faces.

AI has also proven to be useful in detecting other conditions like Alzheimer’s, strokes, various eye disorders and heart attacks. It is even used to choose the apt clinical trial for patients.

How does AI perform with precision

The system is as good as the data you provide it. Scientists develop sophisticated algorithms, in order to comprehend large amounts of data that provide insight into diagnostic patterns that are rather difficult for human beings to identify. It is through practice that AI learns to make precise diagnosis, figure out the associations, analyse the data and produce a favourable outcome.

Even though AI has the capacity to revolutionise the medical field, it faces certain obstacles. To name a few, data sharing and regulations. For an AI to develop and function at its best it needs training with as many data as possible. To execute the AI in real life, it has to meet safety standards and clear strict regulations. The first FDA-approved deep-learning clinical platform is the Artery’s Medical-imaging Cloud AI, which helps to diagnose cardiac diseases.

India too is trying to utilise AI for healthcare in the country. Last year Microsoft announced a partnership with Apollo Hospitals to create and deploy an AI-centric cardiology network. A lot of startups also have started the initiative to acquire AI. This could lead to a better and more efficient means of healthcare.