How Detecting Asbestos With the Help of AI Can Help
The evolution of AI is a vast and comprehensive step in all aspects of life nowadays, and it seems it will change toxin detection as well. People cannot see, smell, or taste airborne asbestos fibers - their size and structure are beyond human sensory perception.
Even identifying them through a microscope requires a trained analyst, but it seems not for long. Engineers are working as we speak on AI technology that can detect asbestos from the air around a worksite, be it industrial or residential.
Last century's prevalent use of asbestos in building materials has caused great suffering among Americans as cases of exposure to airborne asbestos fibers exponentially grew in the past decades. Inhaling asbestos dust is the primary cause of mesothelioma, an aggressive form of cancer exclusively attributed to asbestos exposure.
With the merge of occupational hygiene and robotics, the focus can now shift to detecting various toxins whenever needed, workplaces included. It's a leap in efficiently preventing on-the-job asbestos exposure, although asbestos regulations ensure that it could occur only sporadically today. However, asbestos dust was rampant in industrial settings for decades in:
- construction sites
- refineries
- shipyards
It led to high rates of asbestos-related diseases among many trade professions and exposure cases in home settings. Today, only specialized laboratories can test asbestos materials and identify the presence of toxic material. It created the need for an accessible technology to spot asbestos automatically, and this era is about to give us this solution. In the not-so-distant future, robotics and artificial intelligence could solve asbestos removal and monitoring.
In an asbestos testing laboratory, a technician typically examines a sample through a microscope for about 15 minutes, risking exposure. Meanwhile, a robotic microscope can take hundreds of pictures across an air filter sample in seconds and then upload them to a cloud-based analysis program. The AI then searches the sample for toxic asbestos fibers or any other contaminant at task and generates a report of its findings. And the whole process takes just a few minutes.
It's a bright future for preventing toxic exposure in industrial or home settings, as there's still a risk whenever old buildings are renovated or demolished.
AI Tools Evaluating Asbestos Diseases in a Pilot Study
Patients undergoing treatment for asbestos-caused rare malignancies are now being evaluated using AI in a pilot study. A group of scientists have developed a prototype imaging system that has proved its efficiency with mesothelioma and can accelerate much-needed breakthroughs in diagnosis and therapy.
When it comes to malignant asbestos diseases, the prognosis is poor, and the majority of cases are identified at an advanced stage, considerably reducing life expectancy. Treatment options are limited, and clinical trials are critical for developing new, more effective therapies for conditions such as:
- mesothelioma
- neuroendocrine tumors
- lung cancer
An AI-based system can recognize mesothelioma on CT scans, and this technology is expected to expedite clinical trials of novel medicines. After learning more than 100 CT images that a clinician had previously evaluated, the AI could precisely detect and quantify tumors in CT scans, paving the path for clinical trials of novel therapies with these measures by identifying even small changes in tumor growth.
Moreover, researchers believe that the AI-based evaluation tool would improve the well-being of patients and their families and relieve the workload of caregivers. Although it is still in its incipient stages, AI technology can potentially have a critical role in the future of disease detection, especially cancer diagnosis.