Rising rates of diseases increase the sample numbers pathologists and other medical experts have to deal with, increasing the burden on an already pressured group of healthcare professionals.
This would not be that large a problem if AI was extensively employed. With traditional clinical tools and processes being all that’s used, the burden is pretty substantial.
An AI diagnostics company eases said burden by digitizing pathology to enhance clinical lab workflows and enable more efficient collaboration.
What Is AI in Diagnostics?
AI has become synonymous with support and efficiency in the medical community. In a way it has been the second pair of eyes that never sleeps or goes on vacation. The application of AI has been a blessing to overworked medical practitioners and facilities with reliable support to help maximize workload pressure and maximize efficiency while at it.
In this case, AI is used in the diagnosis of diseases. Using AI in diagnosis is very important because the first step to effective treatment is of course fast, precise diagnosis.
Why Apply AI in Diagnosis
Scale Productivity
When it comes to learning diagnostics, AI remains undefeated. AI is incomparably faster at image analysis and enables the automation of manual, time consuming tasks. This speed allows for case reviews to be much, much faster increasing your lab’s output allowing you to take in more patients. More to my point, the time saved can allow your pathologists to focus on more complex and rare cases.
A study conducted on intraoperative brain tumor diagnosis showed that an expert pathologist could diagnose the issue during surgery in about 40 minutes. With assistance of an AI model in the OR, that time was cut down to under 3 minutes – the difference is staggering.
Increased Diagnostic Accuracy
Pathologists are highly trained, highly specialized healthcare professionals. Be that as it may, the tools at their disposal for case review and clinical diagnostics can be fallible and time consuming. As such, it is plausible for misdiagnosis to occur once in a while.
AI systems improve the accuracy of analysis, reduce bias and standardize sample review ergo democratizing care given to patients. Some statistics for you:
An AI model trained to find metastasized breast cancer tumors was able to detect 92.4% of the tumors. On the other hand, human pathologists’ accuracy clocked in at 73.2%.
The best use of AI is the combining the knowledge and expertise of pathologists with AI’s accuracy and efficiency. Combine these two and you have a better duo than Batman and Robin.
Reduce Costs
By now it is clear as day that AI diagnostics is more accurate than human diagnosis. With AI assistance, bias and subjectivity are completely eliminated. AI systems analyze cases with 100% consistency which reduces diagnostic errors and misdiagnosis.
They even do us one better with more detailed results for better treatment accuracy. It is this sheer precision that directly leads to cost savings.
Misdiagnosis is a rather costly vice costing us both lives as well as significant financial burdens on both patients and hospitals.
Improved Patient Outcomes
Learning diagnostics from AI leads to improved diagnostic accuracy and consistency of analysis. The effects of this accuracy are felt by more than the hospital and pathologists but the patient as well and here is how:
- More personalized therapies can be administered
- Democratization of care given to patients
- Enhanced treatment efficiency
- Reduction of the amount of unnecessary procedures and surgeries
- Enhanced quality of services because patients receive diagnoses faster.
- Enhance staff satisfaction
Services from an AI diagnostics company include better workload distribution achieved by pathologists spending less time on manual, repetitive tasks. The extra time can be spent on assessing cases that require more attention and a higher level of expertise. As a bonus, the burden of rising caseloads is eliminated with faster review times.
