AI Predictions in 2025
Artificial intelligence has been essential to numerous businesses for many years. However, when the word “artificial intelligence” is brought up in the context of healthcare, many people picture robots doing medical procedures on people and making doctors obsolete. Far from being the case, AI has greatly aided the healthcare software development sector and has been essential in establishing industry trends. These important achievements include access to huge data sets that could save lives and forecasts of possible health consequences. Is AI the next big thing in medical software?
According to a Frost & Sullivan analysis, the market for AI systems is anticipated to reach $6 billion by 2021. According to the same survey, healthcare is one of the top 5 industries that will considerably benefit from AI.
What exactly is AI?
Computer systems are used to simulate human intelligence by employing artificial intelligence (AI). Acquiring knowledge, understanding the guidelines for using it, translating it, and self-correcting are a few of these processes.
Software developers have mostly embraced AI in the healthcare industry to create healthcare predictive analytics tools that can transform complex medical data into clear, actionable knowledge using natural language processing.
A few decades ago, AI in the healthcare sector wasn’t as well-liked. In actuality, Dendral, a program created in the 1960s, was the first to include a problem-solving capability. This technology was the foundation for MYCIN, an AI healthcare application that seeks out life-threatening bacterial illnesses. Sadly, despite the achievements made by MYCIN, the program was never used. Hence, it never came to be.
Today, AI development has advanced so quickly. According to the US Department of Health and Human Services, over 80% of US hospitals use healthcare-related software programs. According to a recent survey conducted by Intel and Convergys, more than 50% of healthcare experts anticipate that AI will be widely used by 2020. According to the same survey, 37% of those surveyed already employed AI in some capacity.
Artificial Intelligence in Healthcare
AI applications assist in resolving the healthcare industry’s “iron triangle” problem, where several important aspects converge. Listed below are some advantages of AI in healthcare:
Data Management and Analysis
Within the healthcare sector, a huge amount of data is produced every day. The importance of AI in contemporary healthcare has continued to expand as a result of this rising data velocity and the variety of sources from which this data is gathered.
AI technology has shown promise in improving data utilization, processing, visualization, and decision assistance. AI has significantly improved the modern healthcare continuum by introducing advancements through machine learning and natural language processing, leading to better outcomes.
Researchers have used AI-based software’s robust data processing capabilities to gather, analyze, manage, and store clinical trial data. This methodical technique has made it simple to create new, potent medications.
Diagnostics
According to the Medicine Division of the National Academies of Science, diagnostic mistakes are thought to be the cause of 10% of patient fatalities in the US. However, AI apps have thrived in this field because they can diagnose patients through better data categorization. Additionally, the ability of the AI tool to categorize information has been applied globally to develop ground-breaking therapeutic strategies and even provide advice to medical professionals.
The diagnostic uses of AI can be divided into four main groups, including:
Chatbots: Healthcare facilities employ AI chatbots with speech recognition capabilities to identify recurrent patterns in patient symptoms in order to provide accurate diagnoses, prevent disease, and prescribe the best course of action.
Oncology: Doctors can use a variety of resources to precisely diagnose an illness and recommend a course of treatment, including medical pictures, examination procedures, and patient histories. However, a doctor can only see what their eyes can see, and they might not have the requisite training or expertise to diagnose an illness accurately.
Oncologists use deep learning to find abnormal features in a collection of photos in order to profile and diagnose cancer.
Pathology: Pathology is a branch of medicine that focuses on disease diagnosis through laboratory examination of biological fluids and tissues. Machine learning technologies have improved the tasks and procedures that were formerly the purview of pathologists using microscopes.
Uncommon diseases: To assist doctors in the diagnosis of uncommon diseases, a variety of facial recognition software has been integrated with deep machine learning. Doctors can identify characteristics that match those of uncommon genetic illnesses by analyzing patient photographs.
Surgery with a robot
Using incredibly small tools, robotic procedures provide doctors with a unique chance to make accurate incisions. Almost always, the integration of AI with medical records enables surgeons to obtain current data in the operating rooms as well as helpful data from previously successful surgeries of a similar sort. Accenture projected in a 2018 analysis that AI-enabled, robot-assisted surgeries may save the U.S. healthcare sector more than $40 billion a year.
Medico-legal Communication
Statistics show patients’ and caregivers’ inability to communicate effectively causes 80% of significant medical errors. AI has significantly improved communication breakdown in the healthcare sector, whether it be between the patient and doctor or within several healthcare organs. Apple has developed the CareKit and ResearchKit frameworks, for instance, to assist researchers and developers in creating medical apps that can easily communicate with patients and simultaneously monitor them.
Nursing assistants online
The use of AI in mobile healthcare apps and virtual nursing is another area that has shown outstanding outcomes. Virtual nursing assistants are similar to Alexa for hospital beds in the context of healthcare. By helping the patients with their routines, such as helping them take their pills or make appointments, they mimic the behavior of a typical nurse.
Help with the administrative workflow
Hospitals and other healthcare facilities frequently generate a lot of documentation. However, AI has assisted in the consolidation and digitization of these medical records, simplifying administrative processes.
Healthcare software developers are required.
Many sectors have joined the AI adventure to take advantage of some of the possibilities that come with this technology. Software engineers for the healthcare industry are one crucial component of this rich AI recipe.
Smaller sub-segments of the healthcare sector include robotics, AI diagnostics, patient record management, and equipment software systems. And by developing solutions, software developers can make use of all these domains. This, combined with the healthcare sector’s ongoing modernization of systems and procedures, implies that the demand for developers won’t be slowing down any time soon.
AI’s Role in Healthcare in the Future
AI is gradually encroaching on practically every aspect of human existence. It has established itself as a pillar of coordinated and effective workflows in our businesses. There has been a significant operational and technical makeover, particularly in the healthcare industry.
A closer examination of the present AI-enabled medical software systems indicates significant improvements in performance as well as the quick adoption of software systems across practically all facets of the healthcare sector. The many software and systems designed specifically for the healthcare industry can be modified to do various specialized tasks, including image archiving, hospital information systems, etc.
Future paradigm shifts within the AI ecosystem will make it possible for programmers to create systems with multi-modal interaction. Additionally, due to the proliferation of heterogeneous platforms and devices, platform developers will need to step up their game to target various market segments successfully. This is due to the fact that mobile healthcare computing devices are rapidly gaining ground in the hospital setting and are utilized to improve patient services, care quality, productivity, and costs.
The worldwide healthcare enterprise software industry has surpassed $8.20 billion in terms of growth. Rose from $3.50 billion in 2016. In 2023. The industry would experience an average CAGR of 15.7% during that time, with America being the major market.
Conclusion
Nowadays, technology has allowed us to overcome limitations that were only imaginations just a few decades ago. Healthcare technology advancements, including blockchain healthcare app development, have made it possible for us to work miracles. Real-life cyborgs with technologically enhanced bodies have been produced. Nanorobots that deliver medications through the blood to dangerous target regions have gone even further.
You’ll concur that such a degree of innovation and sophistication would have remained a pipe dream without technology like AI. Despite being hailed as a panacea for earlier disease identification, precise imaging assessment, and economical testing across a variety of clinical fields, the contact between doctors and patients is still a touchy matter. Medical professionals will ultimately need to strike a careful balance between the advantages of AI inpatient management and being in regular contact with their patients.