Revolutionizing Healthcare: How AI is Transforming the Radiology Sector and Improving Patient Outcomes

CXOToday has engaged in an exclusive interview with Amit Gandhi, Chief Business Officer of DeepTek.ai,

Impact on AI in the healthcare sector.

The impact of AI in the healthcare sector, including radiology, has been transformative. AI applications have revolutionized various aspects of healthcare delivery, particularly in radiology, by providing advanced diagnostic assistance, critical condition screening, and quality assurance in radiology reports. These tools offer a significant opportunity to enhance the accuracy of diagnoses, reduce healthcare professionals’ burnout, and ultimately improve patient outcomes.

AI algorithms can analyze medical images and assist radiologists in detecting abnormalities, making their work more efficient and reducing the chances of human error. This not only improves the quality of radiology reports but also expedites the diagnosis process, leading to faster treatment and improved patient outcomes.

Furthermore, the integration of AI into radiology practice has facilitated the shift from conventional to digital imaging, such as computed and digital radiology. This has opened up immense opportunities for healthcare delivery, making radiology services more accessible at the grassroots level and creating robust healthcare delivery mechanisms. The adoption of AI, along with miniaturization of imaging equipment and smart deployments, has further expanded the reach of radiologists and imaging clinics, enabling them to provide quality care to a broader population.

Our goal at DeepTek.ai is to empower radiologists and radiology department administrators with AI-powered tools that enhance patient care, reduce turnaround time, and improve diagnostic accuracy.Our country will never have enough radiologists and this is a great way to scale the skilled.

DeepTek’s solutions have made a substantial impact across the Asia Pacific region serving over 400 customers including government bodies, public and private hospitals, imaging centers, and teleradiology companies.

You’ve reported that your company’s technology has been used to screen over 300,000 people for TB. What are a couple of actual examples of how the technology improved patient outcomes?

DeepTek’s AI powered Lung health screening solution Genki leverages cutting-edge AI technology to classify scans as normal and abnormal along with further analyzing over 19 different chest pathologies. By automating the interpretation of chest X-rays, Genki offers immense potential for improving medical diagnosis and treatment efficiency for lung diseases such as tuberculosis, pneumonia, lung cancer, and chronic pulmonary diseases, all of which pose significant health challenges globally.

In this ongoing TB Free initiative run by Greater Chennai Corporation (GCC) over 300,000 people have been screened since 2019 using the Genki solution, delivering high specificity and sensitivity of 97% as compared to human experts. Also, at GCC, Genki has helped increase the yield of finding TB patients several fold from 20 to 500 per 100,000 screened. significantly increasing the detection rate of TB patients helping in early identification and timely patient care. While playing a pivotal role in our mission to end the TB epidemic; it has also helped us save costs substantially. Taking India a step closer to a TB-free future!

Genki has been instrumental in driving TB-free projects across multiple states, including Maharashtra, Uttar Pradesh, Himachal Pradesh, Gujarat, and Karnataka, solidifying its reputation as a transformative force in the battle against tuberculosis.

Leveraged Across 30+ Districts in APAC including Mongolia, Philippines, Singapore, Tunisia and Thailand.

Genki has already been serving as a lung health screening solution in India and the Philippines and has been instrumental in the ongoing TB Free initiatives in India, where over 300,000 individuals were screened, While in the Philippines, the solution was used during the peak of the COVID-19 pandemic for analyzing people, diagnosing pneumonia (including COVID-19 cases), and identifying other chest pathologies. By reducing the dependency on RT-PCR tests, Genki played a crucial role in optimizing healthcare resources during challenging times.

Trustworthiness is a crucial aspect when considering the long-term viability of AI in healthcare. How does DeepTek address concerns regarding the trustworthiness of AI in healthcare?

As AI is not easily explainable to the medical community, it can be difficult to trust its accuracy and fairness.AI is often perceived as a ‘black box’ wherein the workings and decision-making processes of a model remain hidden, and, therefore, untrustworthy. However, this does not need to be the case.DeepTek.ai emphasizes on transparency and explainability practices to ensure that the workings and decision-making processes of their AI models are understandable to the public. This includes providing documentation of the model training and selection processes, criteria used to make decisions, and measures taken to identify potential risks.

With features such as explainable and interactive AI, fairness and bias review, model decay and drift management, AI performance impact management, and user feedback integration, our solutions enable organizations to build trust, measure RoI, and ensure the responsible deployment of AI solutions.

Moreover, DeepTek.ai places importance on data governance practices during the training phase to ensure that all images meet the same required standards, thus reducing the likelihood of unintentional discrimination in results. This involves determining thresholds for image features such as exposure or lighting to allow for quality images that are easily recognizable by the model.

How will Generative AI impact the healthcare industry?

Generative AI is revolutionizing healthcare by enhancing personalized patient treatments and improving overall care. Medical practitioners have the option to utilize generative AI technology to rephrase patient conversations into a standardized format, allowing for convenient storage, sharing, and analysis. When integrated with Health Record systems, generative AI has the potential to enhance patient communications and provide timely responses to messages. It can simplify complex medical language into patient-friendly summaries, facilitating effective communication.

Generative AI is also playing a significant role in report generation within the healthcare industry. Traditionally, generating medical reports has been a time-consuming and labor-intensive process for healthcare professionals. However, with the advent of generative AI, this task has become more efficient and streamlined.

By utilizing a LLM trained on individual patient information, the system can offer personalized medication recommendations and suggest contextually relevant exercises, ensuring treatments that are tailored to each patient’s specific needs.

Generative AI algorithms are capable of rapidly generating highly accurate 3D models of organs, tissues, and anatomical structures. This technology has the potential to revolutionize the field of radiology, enabling more precise and personalized healthcare.

Beyond clinical applications, generative AI transforms customer interactions in the healthcare industry. Hospitals utilize AI-related technologies and algorithms to increase productivity and improve communication with patients. For example, hospitals in the US have started to employ generative AI/LLM models like ChatGPT to provide directions, answer questions, and offer assistance to visitors. This addresses communication challenges arising from illness, stress, or language barriers, providing necessary support and information to patients and their families.

What role do AI platforms play in the healthcare setup?

The global shortage of radiologists has far-reaching consequences, leading to significant disparities in access to radiology services. In many countries, such as India, the ratio of radiologists to patients is alarmingly low, with only one radiologist available for every 100,000 people. This scarcity results in prolonged waiting times for radiology imaging, which can negatively impact patient outcomes. Fortunately, AI technology offers promising solutions to this problem. AI can reduce reporting times, automate basic tasks, and improve analysis, ultimately bridging the gap caused by the shortage of radiologists.Our solutions Augmento and Genki are a prime example of how AI technology is revolutionizing the radiology industry. With its unique combination of smart reporting and cutting-edge technology, Augmento streamlines workflows, improves communication, and reduces reporting turnaround times of radiology reports.

Augmento, offers an open platform for healthcare providers to integrate AI models developed by DeepTek and other parties into their workflow. This means that healthcare providers can customize their use of AI to suit their specific needs and workflows. Augmento is designed to integrate with FDA-cleared 3rd party AI models into the radiology workflow seamlessly. It helps radiologists and healthcare providers adopt AI tools with minimal disruption to their existing workflow. Currently, radiologists, imaging clinics, and hospitals are adding one AI at a time to the radiology workflow, which can be a time-consuming process; Augmento addresses this issue by creating an AI Deployment Platform, which is a thin client, seamless, and ubiquitous solution.

Chest X-rays are an essential diagnostic tool in detecting a range of chest pathologies, including tuberculosis, lung cancer, and pneumonia. However, the manual interpretation of these X-rays by radiologists and doctors is time-consuming, costly, and can result in errors due to the high volume of cases.

This is where Genki, an AI-powered chest X-ray screening solution, comes in. Genki uses cutting-edge AI technology to analyze chest X-rays and automatically triage patients for different chest pathologies,

including TB. This comprehensive and efficient solution can be used as an offline or online tool in hospitals, health centers, or mobile X-ray vans at hotspots, and also with handheld X-ray machines, making it accessible to remote areas with limited resources, where getting bulky X-ray machines is not feasible.With Genki, abnormals can be separated from normals within a minute, increasing patient screening throughput. But that’s not all! Automating the interpretation of chest X-rays could greatly improve medical diagnosis and treatment efficiency and accuracy not only for TB screening, but also for other lung diseases such as pneumonia, lung cancer, and chronic pulmonary disease which are major health issues worldwide.