Indian Institute of Science

Rumah Sakit Universitas Indonesia to test South Korean AI-powered diabetes management app Kakao Healthcare has signed a memorandum of agreement with state university hospital Rumah Sakit Universitas Indonesia (RSUI) to pilot its latest AI-based diabetes management application. Launched in February, Pasta is a mobile app -based service that leverages AI for blood sugar management. It is integrated with a continuous glucose monitor to display a user's blood sugar level in near real-time. The app also records and stores data on diet, exercise, and sleep, which along with blood sugar information are used to generate automatic lifestyle suggestions. As part of their collaboration, CGMs from Dexcom will be provided for free to RSUI. Data generated from this research will, in turn, help enhance Pasta's AI model. India seeks Google's assistance in AI, digital health tools development India's Union Health Secretary Apurva Chandra recently met with Dr Karen DeSalvo, Google's chief health officer during the 77th World Health Organization's World Health Assembly in Geneva. Chandra is seeking assistance from Google in implementing projects under the Ayushman Bharat Digital Mission (ABDM), India's national programme for building the foundation of its digital health infrastructure. These include the development of AI models and digital tools that integrate with ABDM. Google has been collaborating with the National Health Authority through Google Research since 2022. Their partnership has led to the listing of Google's AI model for diabetic retinopathy screening in the ABDM. It continues today with their joint development of an open-source platform for simplifying integrations with the ABDM. IISc's Centre for Brain Research to try out Wipro's AI/ML for disease management The Centre for Brain Research at the Indian Institute of Science has started working with global IT company Wipro in developing AI/ML and big data-based technologies that assist with the prevention and management of chronic diseases. Wipro is currently designing and building what it calls a "personal care engine" which will be fed with a patient's health history, desired health state, and information on behaviour to provide recommendations on healthy ageing and making positive lifestyle changes. It is intended to help reduce an individual's risk of having cardiovascular diseases and associated neurodegenerative illnesses. The research team tied up with CBR to serve as its trial site for the AI model.

New adjunct specialty facilities in India's leading health institutions are advancing precision medicine in the country through AI. The Apollo Cancer Centre (ACC) in Bengaluru has recently opened what could be the country's first Precision Oncology Centre powered by AI. It offers comprehensive, specialised care that is tailored to each individual. The centre features AI automation to identify eligible patients for targeted therapy and immunotherapy, as well as to alert care teams of patient deterioration. It also deploys conversational AI to educate patients and their families on diagnosis, treatment, and connections to support groups. Additionally, it utilises AI to monitor adherence to standard care; enable patient management based on genomic, clinical, and pathological data; and offer recommendations for diagnostic tests and enrolment to value-based care and other patient benefit programmes. ACC touts that the use of AI, along with harnessing volumes of health data, is the "future of oncology." With AI, it can ensure accurate diagnosis, real-time insights, cancer risk assessment, treatment protocol and continuum of care. Leveraging its expertise in AI, the Indian Institute of Science (IISc), meanwhile, recently launched a collaborative laboratory for AI in Precision Medicine with Siemens Healthineers, a known brand in medical imaging. The lab will develop open-source AI-based tools to automatically segment pathological findings in brain scans. Soon to be integrated into regular clinical workflows, these tools are intended to assist in accurately diagnosing neurological diseases and analysing their clinical impact at a population level. Drs Vijay Agarwal and Vishwanath S, senior consultants of Medical Oncology at ACC, shared with Healthcare IT News more details about their applications of AI in precision oncology. Vaanathi Sundaresan, assistant professor at IISc Department of Computational and Data Sciences and head of the Siemens Healthineers-Computational Data Sciences Collaborative Laboratory for AI in Precision Medicine discussed how they intend to protect sensitive patient data amid growing cybersecurity threats . Q: Can you share specific use cases or applications of AI in your new facility? Dr Agarwal, ACC: There's this one case: a woman with a lump in her breast who visited us for a consultation. Using AI, she was immediately diagnosed with breast cancer within 24 hours of presentation. Following the diagnosis, an automated alert notified all stakeholders – the treating physician, the lead breast surgeon, the multi-disciplinary team (MDT) coordinator and the patient – about the need for an MDT. Once the MDT meeting was held, a recommendation was sent to the centre, and then treatment commenced. The patient pathway was predefined using AI, and all stakeholders were made aware of it. Once the treatment, which includes chemotherapy, was planned, auto alerts were built in for a seamless process of admission, drug ordering, chem prescribing, drug delivery, consents (specific to drug regimens and language), discharge, and payments, thereby improving efficiency and reducing costs. Every change in the treatment plan was relayed automatically to all stakeholders, thereby making the care seamless and well-integrated across all specialties. Chemotherapy and targeted therapy were later advised and then the patient was eventually referred to the MDT. Dr Vishwanath S, ACC: We use AI that f acilitates early, seamless delivery of chemotherapy right from registration, bed booking to discharge. AI also plays a role in facilitating personalised therapy based on NGS (next-generation sequencing) mutation status. In addition, digital pathology and images can be AI-driven – a good example is using bioinformatics and AI to identify a patient with heavily pre-treated advanced sarcoma and an NGS report showing a targetable mutation. A/Prof Sundaresan, IISc: Some other relevant applications of AI that are quite important for clinical deployment include population-level modelling of disease progression, adapting the AI models to be robust towards variation in data characteristics across sites (domain adaptation), limited availability of data (low-data regimes), scarcity of manual labels and outliers. Another important long-term direction would be to identify the relationship between brain health and other organs of the body. Q: What are you planning to be the first project of the collaborative lab? How urgent is the need for precise imaging/diagnosis of neurological diseases and how does AI can support this? A/Prof Sundaresan: Our first project will be the identification of vascular biomarkers on neuroimaging data that would aid in the early detection of neurodegeneration. The prevalence of neurodegenerative diseases (such as Alzheimer's disease and other types of dementia) and cerebrovascular diseases like stroke have been associated with cognitive impairment, gait disturbances, and brain atrophy, which at times can lead to death (with fatality rates up to 47% reported for stroke) and commonly found in subjects with vascular risk factors and depression. AI methods applied to MRI scans can lead to the detection of imaging biomarkers for personalised treatment. However, differential diagnosis and long-term prognosis of such neurological diseases require highly specific imaging biomarkers and thorough investigation of their precise clinical impact – and this is where AI methods can be quite useful. Q: Given the lab's extensive use of sensitive data, how do you intend to secure and protect this data and the algorithms/models that you will apply? A/Prof Sundaresan: Most of the experiments used in the lab will involve publicly available data for initial testing. Any clinical data acquired for the research (from IISc or collaborators) will be obtained after ethical board clearances and will be strictly anonymised and privacy preserved. The methods (without training data) will be open-source for the benefit of the wider research community. _ Their res ponses have been edited for brevity and clarity .

Meds tracking live on Samsung Health Samsung Electronics has started rolling out a new Medications tracking feature on the Samsung Health app to help users manage their medications and improve adherence. The feature helps users keep track of their prescription and over-the-counter medications. It also provides users detailed information about their medications, including potential side effects and adverse reactions, which is licensed from Elsevier. Users can input details such as the colour and shape of their medications, as well as dosage and time of consumption. They can also set up alerts for taking and refilling medications; the feature can prioritise reminders depending on their importance and urgency. Additionally, the feature can also send reminders via Galaxy Watch. Indian researchers develop AI that detects carpal tunnel syndrome A research team from the Indian Institute of Science (IISc), together with Aster CMI Hospital, has created an AI tool that identifies the median nerve in ultrasound videos to diagnose carpal tunnel syndrome (CTS), a common nerve-related disorder. They calibrated a machine-learning model, which was originally developed to simultaneously detect dozens of objects in YouTube videos, to detect just the median nerve. It was trained using ultrasound videos collected from Aster CMI patients with CTS and those who do not have the condition. The AI model can segment the median nerve in individual frames of an ultrasound video, as well as automatically measure the cross-sectional area of the nerve, which is normally done by a sonographer manually. The researchers are now training their AI model to detect all nerves in the upper and lower limbs. It has also been deployed for a pilot test at Aster CMI. CU Medicine doubles down on AI for endoscopic training The Chinese University of Hong Kong Faculty of Medicine (CU Medicine) has recently conducted a study to validate the use of AI in detecting colorectal cancer. The study tested its AI-assisted endoscopic system which was first introduced in early 2021. It was shown that the AI technology, used as a guide by 22 participating endoscopists-in-training, improved adenoma detection by 40%. Meanwhile, CU Medicine also recently introduced AI-Endo, an AI-enabled surgical assistance platform for complicated endoscopic submucosal dissection procedures that remove early-stage gastrointestinal cancer tissues. The platform, according to Dr Yip Hon-chi, associate professor of CU Medicine Department of Surgery, has allowed endoscopists to shorten the training time and proved to be a "reliable" tool to assist the procedure.