A few decades back, the use of artificial intelligence in healthcare seemed like a far-fetched idea. In 2022, AI (Artificial Intelligence) is already being used by many healthcare entities around the world. From surgical practice to clinical diagnostics, AI has several use cases in the healthcare industry. Clinical diagnostics is one sector that is quickly leveraging the power of AI-led tools and solutions. When discussing clinical diagnostics, we mean all the testing processes to detect, monitor, or study human diseases. Clinical diagnostics reports depend on body symptoms, lab results, and signs. Quick treatment is possible only after the detection of the underlying problem/disease. Pathologists are unable to produce better results with outdated tech solutions. Read on to know how AI can be a boon for clinical diagnostics in the 21st century.
AI uplifts the productivity of pathologists
Pathologists are sometimes underrepresented in the healthcare industry. However, the role of pathologists is crucial for the pre-operative procedure. Pathologists are often involved in lengthy medical cases and mundane tasks. With the use of AI-led solutions, a pathology lab can speed up the process of generating test reports. For example, pathologists perform image analysis to detect the underlying problem. Manual image analysis can be a hectic task for pathologists. With AI-led solutions, pathologists can speed up image analysis. AI-led solutions depend on CV (Computer Vision) to understand graphical content. Be it videos or images, AI can offer precise analysis with the least manual effort.
Let us take another example to understand how AI boosts the productivity of pathologists. Sometimes diagnostics are performed during the course of surgery or treatment. If testing or diagnostics is performed during surgery, it is called intraoperative diagnostics. According to a study, an intraoperative brain tumour study takes around 40 minutes. This is a lot of time for a patient who wants to receive the best care immediately. With an AI-led diagnostic solution, intraoperative studies can be completed within minutes. Also, no manual effort is needed to generate intraoperative results with an AI-led diagnostic solution.
AI can boost precision in clinical diagnostics
We all know that human errors cannot be completely curbed. Pathologists have to take care of accuracy during clinical diagnostics. Sometimes, pathologists find themselves in a scenario where one can only predict the underlying problem. When the exact problem in the human body cannot be determined, you want the prediction to be as close as possible. Healthcare predictive analytics software services can help pathologies to be precise. In a recent study, an AI-trained algorithm was used to detect fully-grown breast cancer tumours in the body. The algorithm could detect more than 90% of the breast cancer tumours in the body. With manual efforts and other technology solutions, pathologists can predict around 73.2% of tumours in the body.
If the accuracy of pathologists increases, they can provide surgeons with the best possible results. Surgeons can offer the best possible care to the patient with the help of accurate diagnostics reports. Healthcare predictive analytics AI/ML services software isn’t there to eliminate the need for pathologists. Many healthcare professionals still believe that new-age technologies will eliminate the need for human services. Instead of curbing the need for pathologists, new-age technologies will supercharge the pathologists. Why not choose to perform better and adopt AI in healthcare IT solutions?
AI can reduce clinical diagnostics cost
Pathologies often have to invest in expensive machines and software solutions. Generation of lab reports can get costly at times. What’s the point of expensive machines that cannot even provide accurate diagnostics reports? With an AI-led diagnostics system, a pathology can perform non-stop. Business process automation in healthcare reduced the chances of errors. When a pathology reduces the frequency of misdiagnosis, it will automatically slash operational costs. Not to forget, misdiagnosis can end up taking someone’s life. Misdiagnosis always invites additional costs on behalf of the patient and the pathology. An AI-led solution can perform the work of multiple pathologists without even stopping. Many pathologies think that adopting AI on a wide scale can be costly. Well, many affordable AI-led solutions can reduce clinical diagnostics costs in the long run. As you train AI/ML algorithms, they offer better and more accurate clinical diagnostics results.
Achieve effective workload distribution with AI
With the use of artificial intelligence in healthcare, an organization can distribute workload accordingly. A pathology wants all its employees to be focused and motivated to save lives at all times. It does not mean that pathologists should be treated like workers all the time. At the end of the day, they are also humans and need some assistance at their workplace. AI-led solutions can take responsibility for several mundane tasks from pathologists. After installing an AI-led system, a pathology will experience an immediate rise in staff satisfaction.
Some clinical diagnostics cases aren’t simple and require expert pathologists. You can consider the example of detecting fully grown tumour cells that have spread to different parts of the body. Apart from detecting developed tumour cells, there are many other complex clinical diagnostics processes. For any complex clinical case, AI can reduce the manual burden on pathologists. Digital pathology with the help of AI can significantly reduce turnaround times. AI in healthcare IT solutions will offer a flexible working experience to the staff members.
AI enhances patient recovery and satisfaction
The primary aim of any healthcare organization is to save as many lives as possible. With AI-powered solutions, pathology can play its role in saving lives.
How AI enhances patient recovery and satisfaction is as follows:
- When pathologies will provide accurate and quick diagnostics reports, surgeons/doctors can achieve the desired result.
- Personalized therapies for patients can be administered with the help of AI-led solutions.
- Unnecessary interventions in the treatment due to misdiagnosis can be prevented.
- With AI-led solutions, the intraoperative diagnostic process can be enhanced. Also, healthcare IT support service offerings will boost the pre-operative procedure.
AI tools for digital transformation in the healthcare industry aren’t something latest. It is the result of intrusive research and many years of dedication by medical scientists and experts. Start using AI to improve clinical diagnostics in 2022!