Artificial intelligence (AI) has rapidly evolved in recent years, with applications across almost all areas of life. This includes the healthcare sector.
The emergence of AI in healthcare has completely reshaped the way health professionals diagnose, treat, and monitor patients. Going forward, we can expect sophisticated AI to further revolutionise the industry.
Some examples of AI in healthcare include its ability to find new links between genetic codes, perform robot-assisted surgeries, improve medical imaging methods, and automate administrative tasks.
In addition, AI enables more personalised treatment options than ever before, as well as accurate diagnoses and treatment plans, which enhances preventive care and overall quality of life.
AI in practice
The potential of AI within healthcare is significant.
Not only can it predict and track the spread of infectious diseases, but it can also help combat epidemics and pandemics and speed up the drug research and clinical trial process.
Some processes within the health industry are not always straightforward, meaning there is a gap in the market to automate and improve efficiency.
According to the California Biomedical Research Association, it takes an average of 12 years for a drug to travel from the research lab to the patient.
Only five in 5,000 of the drugs that begin preclinical testing ever make it to human testing, and just one of these five is ever approved for human usage.
Furthermore, it will cost a company an average of $359 million to develop a new drug from the research lab to the patient.
Advanced AI can streamline and accelerate drug discovery and drug repurposing processes, while significantly cutting down time and costs.
A recent trial at the Aberdeen Royal Infirmary explored whether AI can assist radiologists in reviewing thousands of mammograms a year, demonstrating its potential to save a significant number of lives in the coming years.
There has also been a rapid increase in the use of wearable medical devices equipped with AI that can oversee heart diseases at an early stage, thus enabling doctors and caregivers to better detect and monitor potentially life-threatening episodes at an earlier stage.
Therefore, it comes as no surprise that AI in the healthcare market is estimated to grow from USD 14.6 billion in 2023 to USD 102.7 billion by 2028.
Potential challenges at hand
Despite this promise, the adoption of AI in healthcare could cause some challenges.
For example, there could be too much complexity with AI systems, a lack of technology awareness among professionals, and patient confidentiality or data privacy risks.
Without a skilled AI workforce, there may not be enough knowledge around regulatory guidelines, leading to a lack of trust by both patients and practitioners.
Undoubtedly, the large-scale adoption of AI in the health sector will take time and effort, but it has much to offer in the field of medicine and healthcare.
Therefore, it is crucial to establish ethical guidelines and standards, ensure data privacy and security, offer trialability, and educate patients.
Developing trust during the widespread adoption of AI in healthcare is essential.
Like other many other industries, AI will continue to disrupt the healthcare sector.
As innovation takes pace, there will be more opportunities for patient treatment and end of life care.
It is certainly an exciting time for the industry, and it will be interesting to see how much society relies on AI-embedded software in the coming years.
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