Artificial Intelligence For Healthcare

Recently, AI has gained a robust appreciation in various fields to resolve complex issues. The developments and advancements in science have resulted in the adoption of Artificial Intelligence for healthcare, gradually changing healthcare facilities’ operations. In advanced healthcare units such as hospitals, medical research facilities, and clinical laboratories, you will find artificial intelligence being employed to handle complex health issues. Artificial Intelligence for healthcare senses and comprehends data like humans. Since the inception of this healthcare approach, it has enhanced patients’ compliance and engagement with treatment.

Some countries like China have specialised in AI by allocating a lot of money to the AI industry. Other developed countries are joining in to innovate and create AI in various domains. The growth of AI has made the captains in this industry pay more attention to applying this technological advancement in the healthcare sector. AI has made healthcare delivery more efficient and has helped address some of the previously intractable health complications. Artificial intelligence for healthcare is still in its baby steps stage; there is yet a lot to come.

What is Artificial Intelligence?

There are various definitions of AI. Different scientists and experts have distinct perspectives when it comes to the meaning of AI. The below definition sums up different perspectives of AI.

AI refers to installing human characteristics in intellectual processes, reasoning, discovering, generalising, or even learning of past experiences into a computer to achieve certain goals without programming it for a specific action.

The agreement in different definitions is: AI is a device that uses reason, solves puzzles, plans, and communicates in common language by integrating different skills to achieve a specific goal that demonstrates intelligence. We can place human speech comprehension, competition in high strategy gaming systems, driving independent machines, and military simulations in the AI realm.

Artificial Intelligence for healthcare

AI application is becoming common in the field of medicine. AI is being used in the treatment of cancer, and its efficiency in treatment surpasses human expertise. Hanover Project, Microsoft’s entity, has done research that analyses medical treatment for cancer patients in a more personalised way. The National Health Service used the DeepMind platform to discover health risks by using mobile application data and medical images taken from a patient in Britain.

AI in healthcare has proved to perform so well. This contributes to why the use of AI has increased exponentially in clinical environments in recent years. Due to Al having better data mining and advanced recognition capabilities, it has come to solve problems of taking data, analysing it, and applying unstructured data, which is used to diagnose, manage and treat diseases. AI medical applications use symbolic models of different conditions and scrutinise how they relate to patient symptoms. AI in healthcare has also been used to treat protocol development, monitor patients, and develop drugs.

History of AI in healthcare

The discussion of AI in healthcare systems started around 1970 when a physician named Willam B Schwartz, who was very interested in using the science of computing in medicine, published a very influential paper in the New Journal of Medicine. The title of the article is ‘Medicine and the computer. He foresaw the influence of computer science in medicine and how it will change the approach to many diseases and treatment paths.

In 1970, there was already a realisation that the traditional computing techniques applied in medicine could not solve complicated problems. A more advanced model of computing that had a human cognitive phase was developed. This model was Artificial Intelligence. It was placed in medicine to solve complex clinical problems. In 1976, a surgeon from Scotland diagnosed acute abdominal pain using computing analysis. In the 1980s, artificial intelligence research institutions were established globally, especially in the most developed countries.

Application of Al in healthcare

1. AI-assisted image analysis for radiology

The advances in the vision of computers are set to change the area of medical imaging. Doctors use Computed Tomography (CT) images, PET scans, MRI, Ultrasound, and mammography to analyse a patient’s condition.

Through AI, extended technologies in imaging have expanded the ability to analyse images using pattern recognition. This has helped doctors highlight specific image features, identify early signs of cancer, and reduce the process of accurate diagnosis.

2. Predictive analytics for hospital resource optimisation

Another area where AI for healthcare is applied is the administrative demand and supply of healthcare facilities’ resources. Helping ibn break down large quantities of information relating to in-patient treatments, predicting future demand, and allocating budget appropriately.

AI through Al-enabled predictive analytics helps health experts in predicting when and where a certain epidemic will strike. This helps in preparation and planning on how to counter the epidemic.

3. Guiding population-level disease prevention

Having data in which you can tell which population is more susceptible to certain diseases can help put in measures to prevent and curb the spread of the disease. AI has reduced the cost burden to the healthcare system and patients, which rises exponentially when large swathes of the gloomiest generation approach retirement.

4. Machine learning for drug discovery

Drug industries spend a lot of money in billions of dollars every year on failed drug discovery projects. AI in the pharmaceutical field of medicine gives a possibility of producing infinite amounts of drugs, novel proteins, and molecules that machine learning can prioritise, sort, and analyse to know which ones can be viable in the process.

Pfizer, Johnson & Johnson, and Moderna pharmaceutical brands employ vast data science experts to analyse molecular models and chemical actions through machine learning algorithms.

Conclusion

AI for healthcare is rapidly changing the whole health system. Advanced new technologies in medicine help analyse health concepts and develop ways to approach specific ailments making treatment of more deadly diseases easier. Through AL, health experts have been able to classify certain diseases into stages. The classification has helped treat different sets of specific diseases differently, enhancing better management of ailments like cancer, HIV/AIDs, and Diabetes. AI will continue playing a major role in medicine, and in the future, we might get the solution for some diseases like HIV, cancer, and the new coronavirus.