Emerging technology, like AI fused with data, is set to make healthcare more accurate, accessible and sustainable. Imagine a world in which machines not only help but also anticipate the demands of healthcare workers, where massive amounts of medical data are converted into meaningful insights and patient outcomes are optimised with pinpoint accuracy. AI tools have a reputation for aiding and enhancing human labour, rather than replacing physicians and other healthcare professionals. AI is ready to assist healthcare staff with various duties, from administrative workflow to clinical documentation and patient outreach, as well as specialised help in image analysis, medical device automation, and patient monitoring.

Improved disease prediction

Prediction systems use a machine learning model that primarily works on the symptoms given by the user. This is done by using algorithms and the comparison of datasets; thus, we must have the required and sufficient data to compare the symptoms shown by the patients.

AI can be trained to detect mammograms or X-rays that might be missed by human radiologists or during a shortage of hospital staff. Interrogating patients’ records with a highly classified AI tool will diagnose rare diseases much faster, avoiding unnecessary investigations and thus benefiting thousands of patients.

By leveraging technology in healthcare, we can identify ‘at-risk’ patients who require immediate attention and cater to a larger number of patients in a very short period of time to identify abnormalities, detect fractures, and detect tumours.  The more data accessible, the more accurate the AI system will become. The system then analyses this information to detect patterns or trends that may suggest a specific disease or condition. One of the primary benefits of utilising AI for diagnostics is its capacity to continually learn and increase accuracy over time.

Personalised medication and treatment plans

In the age of globalisation, people are mostly on the move. Which makes it a challenge for individuals like her to visit a doctor whenever they are feeling sick. Thus, AI can develop a personalised treatment plan by analysing medical history, genetic data, and lifestyle factors. The advent of machine learning in precision medicine is a revolution for healthcare that enables more tailored medicines with perhaps fewer adverse effects. AI-powered tools also recommend preventive methods to individuals based on specific risk factors.

Even though some patients have experienced positive outcomes from AI for cancer treatment and therapy, many users are scared of leveraging the new technology. 27 per cent of adults in the UK worry about too much dependency on AI for medicine allocation. 60 per cent of Americans are not comfortable with their provider relying on AI-powered technology. But on the brighter side, 75.7 per cent of radiologists believed that algorithmic outcomes based on AI were trustworthy.

Enhanced clinical decision support

As per the writer’s research, AI-based healthcare solutions have seen some of the biggest investments recently. The worldwide healthcare AI industry is anticipated to reach $188 billion by 2030, with a 37 per cent CAGR from 2022 to 2030. Around one-fifth of healthcare organisations have already implemented AI models for their healthcare solutions.

The introduction of AI in healthcare saved around 20 per cent of physicians’ time on administrative activities. About 10 per cent of medical practitioners use AI-powered technologies such as Med-PaLM2 or ChatGPT to provide effective solutions.

Moderna used AI to improve their COVID-19 vaccine. The market for artificial intelligence in healthcare is expected to reach $20.65 billion in 2023.

According to the NCBI study, AI-based algorithms correctly identified 68 per cent of COVID-19-positive cases in a sample of 25 patients previously labelled as negative by healthcare personnel.

Artificial intelligence may serve as a virtual assistant for physicians and nurses. This may involve recommending pertinent medical material, medication interactions, and therapy choices based on the patient’s situation. This frees up significant time for medical personnel to devote to patient engagement and difficult decision-making.

Drug discovery and development

The development of protein-based drugs has reached a concerning stumbling block. Fewer than 10 per cent of such medication ideas are successful in clinical trials. Failure at this late stage of development costs between $30 million and $310 million for each clinical trial, possibly costing billions of dollars per medicine and wasting years of research as patients wait for therapy.

The writer is highly optimistic about the speed-up and boom in drug discovery caused by the increased use of AI because artificial intelligence combined with data may be used to speed up drug development by analysing large bio-databases of chemical structures and biological facts. This might lead to the discovery of novel therapeutic targets and the creation of more effective treatments, but only if we give it the right data.

The cost of discovering new medications will reduce significantly by 70 per cent with increased use of artificial intelligence and data science. The majority of the money AI produces in healthcare comes from the United States. It had a 58 per cent market share in 2022, with Asia-Pacific coming in second at 40.9 per cent. However, AI in healthcare statistics shows that 90 per cent of nursing tasks will still be performed by humans in 2030.

Skin cancer screening is one area where the public believes AI might be useful, with 55 per cent of respondents believing it would be even more accurate than traditional screening.

Administrative efficiency and cost reduction

Artificial intelligence can easily automate repetitive processes like appointment scheduling, claim processing, and data input. This frees up staff time to focus on more complicated duties, resulting in increased operational efficiency. Additionally, AI-powered solutions can assist in identifying and preventing fraudulent medical claims, resulting in cost savings for healthcare providers.

Advanced chatbots or AI-powered AI nursing assistants are expected to save $20 billion per year by reducing the 20 per cent of time nurses spend on patient maintenance tasks. Sensely’s “Molly” chatbot demonstrates this by asking patients questions, assessing their symptoms, and sending them to the appropriate resource. These days, more and more individuals are employing AI chatbots, such as ChatGPT, to obtain therapy without requiring human interaction. Now that AI therapy is so popular, 40 per cent of Americans would choose to use it instead of seeing a human therapist in person.

The future of AI in healthcare

Even though healthcare took up artificial intelligence and machine learning a bit later than other industries like manufacturing and trade, The writer cannot emphasise more on the bright future of artificial intelligence in healthcare. However, she shows concern over ethical considerations around data privacy, bias in algorithms, and the need for human oversight, which should not be ignored.

It is a piece of great news for cancer patients because AI algorithms can predict cancer patients’ survival with an accuracy of 80 per cent. Researchers at the University of British Columbia developed an artificial intelligence (AI) model that can recognise patient traits from oncologists’ notes and predict cancer survival with 80 per cent accuracy.

AI has the highest accuracy for detecting early indicators of dementia. CognoSpeak, an artificial intelligence tool, can detect Alzheimer’s disease 90 per cent of the time by analysing patient language and speech patterns, equivalent to traditional approaches.

Oncology and neurology will be the dominant fields in AI-powered precision medicine. In 2022, oncology (cancer diagnostics) accounted for more than 31 per cent of the revenue in the precision medicine market. Over the next 10 years, neurological disorders such as dementia and epilepsy are predicted to increase and dominate the market.

Artificial intelligence-powered robot surgery might cut patients’ hospital stays by more than 20 per cent. According to the writer’s studies, an artificial intelligence robot reduced problems in orthopaedic surgery by five times more than doctors working alone. Furthermore, this might result in a 21 per cent reduction in patients’ hospital stays following surgery. Subsequent savings are expected to total $40 billion each year.

Thus, it is very important to innovate in the healthcare landscape with AI to stay ahead of the race.

The writer completed her post graduation from Queen Mary University of London, and is a computer science engineer from Techno India University, Kolkata, India