Automated Pathogen Detection is set to transform pathology and here is what you should know about it

52-year-old Rakesh Singh walks into a primary health care center in rural Rajasthan with what seems to be a suspected case of Tuberculosis. After hours of waiting in line, his sputum sample is collected and sent to a lab for a sputum smear microscopy. Days go by but Rakesh’s results turn out to be inconclusive, and his diagnosis and line of treatment are subsequently incorrect. Although Rakesh’s case is fictional, the reality of TB in India isn’t. According to the WHO, India recorded about 2.69 million cases of TB in 2018 and the country’s caseload is the highest in the world.

What if there was a way to make TB diagnosis better, faster and error-free? What if there was a way to fine tune the process of sputum smear microscopies? Here is where Artificial Intelligence (AI) and Automated Pathogen Detection hold some answers.

Automated pathogen detection might sound like futuristic words out of a medical lexicon, but thanks to advances in AI, it is fast becoming a reality in laboratories across the world. In essence, Automated Pathogen Detection is a process that combines the power of AI and automation to help test samples of human tissue, sputum etc. in a faster and more accurate manner by eliminating the need for manual human labour. Take for example the process of a Sputum Smear Microscopy (SSM), which is still the primary method for diagnosis of pulmonary tuberculosis in developing countries like India. For an SSM, sputum collected from a patient’s lung is placed on a slide and stained to highlight the bacteria which are then counted by hand. The process of counting thousands of tiny strains is extremely tedious, manual, and time-consuming.

Automated pathogen detection that is aided by advanced artificial intelligence offers a revolutionary solution to this. Vision-enabled AI software can help analyze microscope output that is fed from digital cameras as video. The video is then converted into a series of images and the bacterial load is identified and counted from these images. Aided by AI neural networks and a workflow that is augmented by vision intelligence, the possibility of human error is completely weeded out and samples can be tested 24×7 at a much faster rate. Tuberculosis is just one of the myriad examples; AI-augmented workflow is now also beginning to play a pivotal role in cancer diagnoses wherein tissue biopsy samples can be analyzed more pertinently and effectively, leading to potentially life-saving diagnosis. And in the years to come, AI-aided workflow will find more applications in diagnostic pathology.

One of the main reasons why technologies like Automated Pathogen Detection are finding a stronger foothold in medicine is because they help tackle the decades-long challenges posed by traditional pathology. Medical professionals have been sounding the alarm about scarcity of pathologists and the issues with physical storage of slides in diagnostic pathology for many years now. India, for example, has a load of nearly 40 million sputum samples that are collected annually, and the volume is only set to increase year-on-year. Proliferation of AI-based technology could mean that images of slides don’t need to be physically stored and instead, they can then be digitally archived and even printed in a report. AI-augmented workflow is also largely operator-independent and requires very little human intervention. This could mean that low and middle income countries like India that have a shortage of skilled pathologists need not lose out on high quality and accurate diagnosis. AI-augmented workflow that is empowered by vision intelligence has the potential to address these and a host of other challenges in medicine.

Apart from being a game changer in diagnostic medicine, Automated Pathogen Detection is also the perfect embodiment of the promises that new-age tech, AI, and automation hold. In an article developed by the World Economic Forum, it was envisioned that in the Fifth Industrial Revolution, humans and machines will dance together! This of course is metaphorical, but it perfectly encapsulates the essence of technology such as Automated Pathogen Detection that is not meant to replace pathologists but instead support them and help them make rapid and accurate decisions that can save lives.

SLIP, TRIP, FALL – Four-letter problems with a 4-letter solution

One of the leading causes of workplace injuries is STF – an abbreviation for the three dreaded words, namely Slip, Trip, and Fall. In Australia, there are more deaths from Slips, Trips, and Falls than there are from fires. In the USA, more than 2000 people need emergency medical care after a slip and fall accident every day, the medical bills for which can often run into astronomical figures of USD 30,000 per case. On an average, 11 working days are also lost as a result of slip and fall injuries. Hence, it is no wonder that insurance claims for incidents involving STF run into billions.

Most STF cases are caused by a lack of active monitoring and shortcomings in safety practices. In fact, negligence is identified as the main reason for STFs and proving it is the easiest route for an accident victim to claim compensation. It is now acknowledged that Slip and Fall accidents are a public health problem because they are so common and costly.

Many slip and fall accidents are preventable and several nations have guidelines for employers to keep workplaces safe and minimize the chances of accidents. If businesses and individuals take the initiative to keep their property safe for customers, other guests, and employees, then they can take preemptive action and prevent these accidents before they happen.

This is where AIVI (Vision enabled Artificial Intelligence) can play a leading role.  AIVI is a technology platform developed by AI experts Cogniphi; it enables an easy and practical solution that can help to continuously track, monitor, and send out real-time alerts whenever there are any shortcomings in safety practices at work places. Be it a poorly lit corner or a slippery surface or a poorly maintained walkway and badly stacked goods, AIVI technology can detect these problems and flag them before disaster strikes.

The AIVI Artificial Intelligence software, which harnesses the power of Computer Vision and Data-driven Learning, works with existing or newly installed camera hardware to detect anomalies in a series of existing conditions and practices followed at retail outlets, factory floors, gas stations, hospitals, nightclubs, or any other workplace. Through its Machine Learning capability, AIVI filters approved conditions and keeps updating itself so as to fine tune its algorithms for pattern recognition and become a literal third eye that warns you of inadequacies in real-time. Solutions deployed can also be taught to learn new patterns and anomalies, and adapt to varying needs as well as build predictive systems.

Even in cases where a Slip, Trip, and Fall does happen in a situation monitored by an AI-enabled video, the instant detection of a Fall can be rapidly relayed to the authorities concerned and illicit a quick response instead of delayed medical care. Timely handling of an STF injury can lead to lesser damage for the person and company.

Talk to Cogniphi and get a further feel of how Vision Intelligence can predict and prevent STF accidents and save your business immense loss caused by Negligence.

Ushering in a new era of Healthcare with Vision AI

The global pandemic has forced us to rethink our existing healthcare system and has created a need to harness advances in technology. Vision-enabled Artificial Intelligence (AI) that combines Computer Vision and Machine Learning (ML) has the proven technologies and potential to improve patient care and hospital efficiencies.

With increasing disease complexities, rising expenses and shortcomings in infrastructure, the healthcare sector needs a panacea for development and growth. By deploying Vision AI, with little addition to existing infrastructure, hospitals and clinics can bring about a system of continuous quality improvement and make healthcare more accessible and inclusive.

The primary areas of Healthcare that are leveraging cutting-edge advances like Vision AI quicker than any other are research, diagnostics, health monitoring, treatment, patient outcomes, Covid protocol monitoring, and facilities management. Here’s a brief look at how.


Research, Diagnostics, Health Monitoring and Treatment

Vision-enabled AI, by developing patterns and correlations in events and data, paves the way for research discoveries that can be life-saving, and also help in error-free and speedy diagnosis that leads to precise and enhanced treatment.


What ML does is it provides, by identifying certain critical patterns and signals that the human mind might miss, an extended arm to the doctor to fine tune his interpretation of available medical data. Further, advanced video analytics, by providing facial analysis and subtle clues about a patient’s behaviour, can often enhance the physician’s own expertise to get an accurate understanding of what a person is actually experiencing, and ensuring that nothing goes unnoticed.


Elevated Patient Satisfaction



AI-driven innovations hold great potential in connecting better with patients by delivering more personalized care and streamlined services. By tracking nursing care to needy patients, patient mobility, tendency to wander from the bed zone, discomfort, injury-prone situations and unusual behavior, Vision AI is already playing a critical remote control role in the vital areas of Patient Safety and Patient Satisfaction. On the advanced technology front it is not far away that Vision-based patterns and insights on patient distress (through face expressions) will help detect instances of Shock or Cardiac so that critical medical attention can reach him in time.


Adherence to Safety protocols

The pandemic is driving changes in hospital safety and this is where the application of Vision AI can be effectively implemented straight away. Compliance monitoring in health centres is now automated and remotely controlled through practical applications that account for the importance of touch-free, contact-less in-patient care.


Vision AI, for instance, helps in tracking glove, gown, and mask utilization, and in analysing utilization of hand sanitizers/hand hygiene. These applications are now available to continuously check patients, hospital staff, vendors and visitors for all contamination protocols to ensure compliance throughout critical areas. It can detect and alert, in real time, patient flow and crowding of waiting rooms and corridors such that compliance protocols are not violated.

Quicker Turn around

At a time when hospital occupancy is at an abnormal high, making room for more patients has also become a top priority. In large facilities operational efficiency jumps multi fold by automating room assignment, tracking room turnover step-by-step, and detecting the true cause of delays.Vision Intelligence can easily be integrated with existing facilities management systems to remotely monitor patient discharge, room cleaning and readiness so as to reduce turn-around time to the minimum and optimize patient flow.


The global COVID-19 pandemic has opened our eyes to the need of better support to our hospitals and essential frontline workers who risk their lives to keep us healthy and safe. As AI is increasingly becoming a part of our daily lives, it is time we harness it to build a smarter and more connected healthcare system that benefits all of us, every day.