AI-driven systems improve testing capabilities as they provide advantages for clinical lab studies by looking at the microscopic view precisely. With AI based analysers, labs can improve testing efficiency, report accuracy and save TAT to improve patient care.
Artificial intelligence has proven to be extremely effective in diagnostic analysis and study. AI-driven systems like AI100 analyser when utilised in a lab improves testing efficiency. Over the years, the diagnostic industry has been evolving to introduce better technological systems to improve the accuracy of results. This further helps in improving quality of care to patients across different healthcare networks. AI-systems can be quite beneficial to meet such end-goals in a laboratory setting.
How AI helps in sample analysis?
AI systems with its robust image processing capabilities can be helpful in early detection, analysis and decision making at testing. It also helps plug several analytical challenges in a traditional lab workflow. Some of these include waiting for a pathologist visit the lab in person to spend time on each slide to derive conclusions. For multiple lab consultation, it is quite difficult for them to offer their pathological assistance in time.
On the other hand, for histopathology tests, genetic testing and other multi-stage testing procedures, the TAT is quite high. All such challenges can be minimised or in some cases eliminated using AI analysers for testing.
Introducing AI100 Analyser for quality lab studies
AI100 analyzers designed with solutioning applications, Shonit (for blood morphology) & Shrava (for urine morphology) allows you to cater types of hematology and clinical pathology tests to generate accurate test results.
They convert biological samples on a slide into digital images that are further shared across to a pathologist or a group of pathologists for analysis using a secured cloud platform. This enables faster approval, reduces manual workload and as well as testing errors.
Reporting using AI100
Once the study is complete, the system auto-enters values into the reporting software. These reports are shared remotely with pathologists for validation and approval. Critical test results are mainly prioritised to reduce patient’s waiting time to get aid. Also, remote report validation & approval allows doctors to approve reports even after working hours, weekends and holidays. This helps to control the overall analytical and post-analytical TAT for the lab.
How does cloud storage of study images help?
- Storing study images on the cloud helps in future analysis of chronic cases. This saves the trouble for long-term sample storage especially when samples are likely to perish.
- Saves logistical cost for transferring archived samples. Sharing images digitally requires zero cost as compared to sample transfer logistics, storage and preservation.
Advantages of using AI100
- Can be integrated with LIMS or lab reporting software to generate accurate & quality results.
- Reduces redundant tasks, improves productivity and increases throughput by 66%.
- Automated workflows using AI systems reduces up to 90% TAT as compared to a traditional workflow.
- Improves testing efficiency especially for special, rare and extreme cases.
- Saves up to 54% outsourcing cost.
- Maintains reporting consistency.
- Reduces eye strain and fatigue to pathologists.
Upcoming analyser applications
The upcoming analyser applications by AI100 include:
- Universal Scanner (Scans any and every sample that can be viewed under a microscope).This feature can be used extensively for telepathology.
- Semen Analyser
- Bone marrow
- Body fluids