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Pharma Tech Outlook | Monday, June 22, 2020
As the entire world is being digitized technologically, continuous efforts are being put into making analyses and diagnoses easier and more accurate with better recovery techniques. This is where the combination of AI and digital pathology is making its way through the medical field and beyond to assist in medical research and practice.
Fremont, CA: As digital pathology invites a number of technologies, Artificial Intelligence (AI) is leading the queue. Handling large sets of data with more accurate and precise analyses is now easier for scientists with the introduction of AI. Not just handling them but sharing the data or results with other researchers has become easier. It is expected that digital pathology will set up a new trend in the healthcare and medical system.
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From $689 million in 2018, the digital pathology market is predicted to rise by 11.7 percent by 2026.
Image analysis using AI
The core concept of digital pathology lies in imaging the samples, digitizing them, and sharing them digitally. AI aids in the improvement of digital image analysis. In the domain of oncology, the amalgamation of AI and digital pathology has been very effective. Measures of HER2/neu, estrogen, and progesterone receptors are the clinical indicators of breast cancer. The trained computer programs help in recognition and assessment of the indicators, along with the assessment of Ki67 in a malignant tumor.
[vendor_logo_first]It is believed that AI can considerably speed up the development of a drug by assessing the effectiveness of the drug composition. Moreover, AI reduces a large amount of manual labor that has to be invested in slide image analysis. Manually selecting the area of study is automated by AI, which not only helps to deal with larger slides but also accelerates the diagnosis.
Integrating AI in clinical data handling
When it comes to the data, there are multiple sources such as historical clinical data and data from histopathology and demographics. Most of the time, these data are unstructured and in different formats. AI can play a significant role here in data integration. In addition to this, natural language processing has helped in deciphering information from handwritten data sets and attaching those with image analysis results.
Making the analyses error-free
Since the beginning, diagnoses and different test results have been dependant on the expertise of the analysts or researchers. Despite that, these analyses are always prone to manual errors. With proper machine learning, when the analyses are performed automatically, the chances of human errors are erased. Apart from this, as AI makes sharing easier, any of these images can be shared with multiple experts for their judgments, and hence the accuracy levels go up. The inferences in reports are also verified using AI.
The scope of AI will reach its peak in digital pathology, making it the most accurate and optimum. With the speedy advancement in technologies, especially AI, the world is hopeful to witness a better and more efficient medical and healthcare with its potential to speed up drug development, more accurate analyses and higher standards of the healthcare system.
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