Reasons to Implement Artificial Intelligence in Diagnostics|AI in Pathology

Reasons to Implement Artificial Intelligence in Diagnostics|AI in Pathology

Rising diseases like cancer, increase sample numbers, putting an additional strain on pathologists, an already underrepresented group of healthcare professionals. The problem is exacerbated by the fact that pathologists’ traditional clinical tools and processes are manual and subjective. In this blog, we discuss reasons to implement AI in diagnostics.

Digitization of pathology has aided in addressing some of these issues by improving clinical lab workflows and enabling more efficient collaboration. AI has to be implemented to make processes easier, less time-consuming, and accurate. Only then diagnostics can benefit from digital pathology solutions. After all, effective treatment starts with an accurate and timely diagnosis.

Increase Productivity

AI is much faster at image analysis and allows for the automation of manual, time-consuming tasks. Accelerating case review increases the output of your pathology labs, allowing for more new patients to be admitted. Pathologists can also devote more time to complex and rare cases because of the time saved.

A study on intraoperative brain tumor diagnosis discovered that an expert pathologist’s diagnosis during surgery, which usually takes 40-minutes, can be completed in under 3 minutes with the help of an AI model in the operating room.

Improve Diagnostic Precision

Pathologists are highly specialized healthcare professionals, but conventional diagnostic tools and processes are slow and have various restrictions. Artificial intelligence systems improve analysis accuracy, reduce bias, and standardize sample review. An AI model trained to detect metastasized breast cancer tumors detected 92.4% of the tumors, compared to 73.2% for human pathologists. The most advantageous application of AI is the combination of a pathologist’s knowledge and AI’s accuracy and efficiency.

Cut Down Costs

AI-assisted diagnosis improves diagnostic accuracy by removing bias and subjectivity. Cases are consistently analyzed by AI systems. Reduced diagnostic error and wrong diagnosis together with enhanced and accurate treatment will result in thoroughly detailed results. In turn, reducing costs and giving out precise results. Misdiagnosis not only claims lives but also places a significant financial burden on both patients and hospitals.

Improve Employee Satisfaction

Pathologists can achieve better workload distribution by spending less time on manual, repetitive tasks and more time assessing rare or complex cases that require a higher level of expertise and skills. Faster review times reduce the overall burden of rising caseloads.

Improved Diagnostics

The improved diagnostic accuracy and consistency of analysis provided by AI assistance benefit not only the hospital and pathologists, but most importantly it helps patients. The following are the outcomes:

  • Improved treatment efficacy.
  • More personalized therapies will be used.
  • Lowering the number of unnecessary interventions or surgeries.
  • Patients’ care is being democratized.
  • Improved service quality as patients receives diagnoses more quickly.
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