Diagnostic Devices
Cuff-less Blood Pressure Estimation
Tata Elxsi Use Case
Use Case: This innovative approach uses machine learning to estimate blood pressure in real-time from PPG and ECG signals, removing the need for traditional cuffs.
How it Works: Extensive feature engineering from publicly available medical datasets, creating 60 models to cover various blood pressure categories. It reached an error of <10 MAE on public datasets and ~16 MAE on live data, demonstrating its efficacy for non-invasive monitoring.
Tech Stack
- Machine Learning algorithms
- Feature engineering techniques
- Microcontroller deployment for real-time application
AI-enabled Detection and Classification of Heart Sounds
Tata Elxsi Use Case
Use Case: An AI-driven solution which leverages digital stethoscopes and hospital data to detect and classify heart sounds, distinguishing murmur sounds from normal heart activity. It accurately identifies various conditions like Aortic and Mitral regurgitation or stenosis, providing critical data such as Ejection Fraction (EF) and Cardiac Output (CO).
How it Works: The system analyses heart sound data, including pitch, THD, Q-Factor, and Cepstrum statistics, to classify murmur sounds by type and intensity, from grades I to VI. This advanced classification aids in early diagnosis and treatment planning.
Tech Stack
- Digital Signal Processing (DSP)
- Machine Learning algorithms
- TensorFlow or PyTorch
- SciPy for scientific computing and signal processing
- Keras
- Audio processing libraries
Digital Therapeutics
Glaucoma Detection using Computer Vision
Tata Elxsi Use Case
Use Case: Designed to help medical practitioners to identify Glaucomatous changes that takes place from Fundus images of the retina, achieving a first-stage target accuracy exceeding 90%. It employs state-of-the-art AI algorithms for medical image processing, ensuring accurate and efficient detection of Glaucoma-related anomalies.
How it Works: By harnessing AI models meticulously chosen and refined with clinical insights and patient data, the system continuously evolves through ongoing scrutiny and adjustment by medical experts. This iterative approach not only bolsters detection accuracy, it can also ensure steadfast performance in identifying Glaucomatous changes from Fundus images.
Tech Stack
- Deep Learning and Computer Vision
- Convolutional Neural Network, Recurrent Neural Network, Restricted Boltzmann Machine, Multilayer Perceptron, TensorFlow, Keras, PyTorch
- Sci-kit library models
- Automated Machine Learning
AI-based Screening for Malignancy Detection
Tata Elxsi Use Case
Use Case: By using neural network models to distinguish malignant cells from normal ones, can help enhance early malignancy screening. This process integrated within diverse medical images, streamlines diagnotic journey offering more accurate identification of potential malignancies.
How it Works: By analysing microscopic slides and radiology images collected on a large scale, AI models identify abnormal patterns indicative of hematological malignancies and other disorders, facilitating early detection of various cancers through visual imaging.
Tech Stack
- Neural networks
- Machine learning algorithms
- Image processing techniques
AI-based Interactive Avatar for APD Devices
Tata Elxsi Use Case
Use Case: APD devices like Amia and Claria, while revolutionary, present a challenge for first-time users. Trained nurses are required for device operation. Patients often need to refer to manuals or make repeated calls for assistance. This innovative solution is an AI-based Avatar that verbally interacts with patients, answering queries, providing information, and facilitating data collection. This helps in enhancing user experience and device comprehension.
How it Works: The AI-based Avatar revolutionises patient interaction and engages patients verbally, addressing queries related to peritoneal dialysis devices. It alleviates the need for multiple manual kit consultations or assistance calls, as the Avatar collects vital data. With fast and accurate responses, support for multiple languages, and internet independence, the Avatar enhances overall user experience.
Tech Stack
- Machine Learning Algorithms
- Natural Language Processing (NLP)
Voice Recognition Systems - Fast Response Processing
- Multilingual Support Systems
- Internet-Independent Communication
Robotic and AI-assisted Surgery
Image Analytics for Detection of Blood Loss During Surgery
Tata Elxsi Use Case
Use Case: This technology accurately assesses blood flow intensity, classifying it on a scale from mild to life-threatening. It aids surgeons in reducing intra-operative and post-operative complications by selecting the optimal topical hemostatic product.
How it Works: The system leverages visual analytics to monitor blood flow, colour, and quantity in real-time during surgery. It employs a lightweight AI architecture that classifies blood loss severity and recommends the appropriate sealant, thus improving clinical decisions.
Tech Stack
- Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Restricted Boltzmann Machine (RBM), Multilayer Perceptron (MLP), TensorFlow, Keras, PyTorch
- Sci-kit library models (SVM, XGB, FPGrowth, Clustering, Random Forests, Decision Tree, Regressions)
- Automated Machine Learning
I3D network: Inflated 3D ConvNet
Pharma
ML-based Pharmaceutical Instrumentation
Tata Elxsi Use Case
Use Case: ML algorithms digitise pharmaceutical test instruments, like membrane filter testing. This helps in significantly boosting accuracy and efficiency, reducing result generation time to just 20% of traditional methods.
How it Works: The integration of ML techniques optimises the testing process, enabling rapid analysis and interpretation of data. This helps to dramatically accelerates the delivery of results without compromising on precision.
Tech Stack
- Machine Learning algorithms
- Data processing and analytics tools
- Integration platforms for instrument digitization
Gen AI-based Smart Clinical Trials
Tata Elxsi Use Case
Use Case: The platform revolutionises clinical trials through a customised digital solution for decentralised trials and CRO site management. It enhances transparency, reduces costs, and ensures efficient participant retention. The ability to scale at your needs brings about increased efficiency, visibility, and data quality. Real-time reporting, remote user assistance, and reduced operational burden further characterise this user-friendly platform.
How it Works: Custom machine learning algorithms drive participant engagement, optimising the clinical study experience. Seamless enrollment, automated engagement, and real-time tracking enhance efficiency. The system integrates data from diverse sources, fostering transparency and scalability. Study and site coordinators utilise real-time tracking and reporting, simplifying interactions for an innovative and streamlined approach to clinical trials.
Tech Stack
- Machine Learning Algorithms
- Blockchain
- Cloud Computing
- Natural Language Processing (NLP)
- IoT Devices
Patient Care
AI-based Intra Oral Camera
Tata Elxsi Use Case
Use Case: This AI-based solution revolutionises intra-oral care by utilising an oral camera unit for automated detection of cavities and tooth or gum diseases through advanced image analysis.
How it Works: Patients bite into a semi-circular groove of the oral camera unit, allowing multiple cameras to capture images of the tooth surface simultaneously. These images are then analysed by a neural network to identify dental issues quickly, reducing the need for extensive dentist involvement.
Tech Stack
- Neural networks
- Image processing algorithms
- Multi-camera integration for comprehensive dental imaging
Digital Health Platform for Autism Therapy
Tata Elxsi Use Case
Use Case: Offering custom behavioral therapy modules, interactive learning tools, and communication aids, DHPs cater to autistic individuals. These digital tools, designed to complement traditional therapies, deliver consistent, engaging, and personalised interventions. Transforming the landscape of autism care, DHPs ensure a tailored approach, enhancing therapy outcomes.
How it Works: DHPs leverage artificial intelligence to provide tailored behavioural therapy modules, interactive learning tools, and communication aids for autistic individuals. These digital interventions seamlessly complement traditional therapies, offering consistent, engaging, and personalised support. The AI-enhanced approach ensures adaptive and effective interventions, transforming the autism therapy landscape with a focus on individualised care.
Tech Stack
- Machine Learning Algorithms
- Natural Language Processing (NLP)
- Customised Behavioural Modules
- Interactive Learning Tools
- Communication Aid Technologies
Yoga Posture Tracking and Correction
Tata Elxsi Use Case
Use Case: This iOS-based application elevates the practice by intelligently identifying users’ poses and providing corrections, ensuring proper alignment and safety during workouts.
How it Works: Leveraging deep learning AI for posture tracking and correction, the app offers personalised Asana recommendations based on medical history, real-time flexibility scoring, and voice-based corrections. It supports goal-based programs for holistic well-being.
Tech Stack
- Deep Learning
- Voice recognition for interactive guidance
- Data Analytics
Risk-based RoI Assessment for MedTech
Tata Elxsi Use Case
Use Case: Risk-based RoI Assessment for MedTech focuses on enabling payer clients to reduce medical costs by preventing adverse healthcare events such as hospitalisations and emergency room visits. This strategy aims to improve patient health outcomes, enhance medication adherence, and boost total revenue through effective risk stratification and personalised care decisions.
How it Works: The solution employs a risk-based contract approach where Care Management Services (CMS) commits to monitoring a specific subset of a payer’s population, aiming to reduce per member per month (PMPM) healthcare costs. Through risk stratification and advanced data analytics, CMS can identify high-risk individuals and intervene early, ensuring a significant reduction in healthcare costs and guaranteeing a positive return on investment (RoI) with a favorable ratio.
Tech Stack
- Risk Stratification (ACG)
- Tableau Visualisation
- Machine Learning Algorithms
- Big Data Platforms (e.g., Hadoop, Spark)
- Natural Language Processing (NLP)
- AWS/Azure
- Python (Pandas, NumPy, Scikit-learn)
- SQL Databases (e.g., MySQL, PostgreSQL)
- Blockchain
- Snowflake
Education and Training
Human Anatomy using Digital Twin
Tata Elxsi Use Case
Use Case: Digital Twin leverages augmented reality (AR) and artificial intelligence (AI) to transform medical education. This advanced tool enables interactive learning of complex anatomical structures, offering a personalised and engaging educational experience that enhances understanding and retention.
How it Works: AI algorithms create dynamic 3D/4D anatomical models from medical datasets, adapting learning content to individual needs. Natural language processing allows for interactive queries, while machine learning tailors the educational pathway, ensuring personalised and efficient learning. AI-enhanced AR visualisation provides immersive, hands-on experiences.
Tech Stack
- Augmented Reality (AR) platforms
- Machine Learning
- Natural Language Processing
- Computer Vision
- 3D/4D Visualisation Software
- Data Integration Tools
Hospitals
Patient Posture Detection using Image Analytics and ML
Tata Elxsi Use Case
Use Case: Utilising image analytics and machine learning algorithms, the system detects patient postures and generates actionable insights for caregivers, achieving over 90% accuracy even with limited training datasets. It enables timely care to prevent emergencies and supports multiple patient monitoring, significantly reducing response times in critical situations.
How it Works: Detecting the number of patients in a room and their postures, it utilises facial recognition and emotional analytics for individual tracking. Automatic alerts are triggered to caregivers in case of an emergency or significant emotional state changes, facilitating immediate and appropriate medical responses.
Tech Stack
- Convolutional Neural Networks (CNN)
- Recurrent Neural Networks (RNN)
- Support Vector Machine (SVM)
- TensorFlow and Keras
- PyTorch
- OpenCV
- Machine Learning algorithm
Bacteria Colony Enumeration using AI
Tata Elxsi Use Case
Use Case: Leveraging AI, this solution uses state-of-the-art deep CNN architectures to accurately identify and count bacteria colonies on Petri dishes, despite the challenge of a limited dataset.
How it Works: By standardising data annotation with microbiologists’ insights and optimising algorithms for embedded boards, the solution achieves remarkable timing performance. This ensures fast, efficient analysis suitable for real-time applications.
Tech Stack
- Deep Convolutional Neural Networks (CNN)
- Single Board Computer with NVIDIA Pascal GPU
- Custom algorithms optimised for high-speed processing
Regulatory Compliance
Gen AI-based PFAS identification and Impact Analysis
Tata Elxsi Use Case
Use Case: Leveraging Gen AI for PFAS (Per- and Polyfluoroalkyl Substances) identification and impact analysis streamlines supplier coordination, data collection, and regulatory strategies. This helps to assess and mitigate risks associated with PFAS in product portfolios.
How it Works: The process begins with supplier outreach and data collection, followed by extensive data review and analysis to create detailed impact reports. This informs regulatory strategies, supports lab testing for chemical characteriszation, and guides the identification of safer alternative materials.
Tech Stack
- Generative AI
- Database management systems
- Analytical tools
Gen AI-enabled Post-market Surveillance Report Creation
Tata Elxsi Use Case
Use Case: Gen AI streamlines post-market surveillance report creation in medical device regulation, automating literature surveys and data collection to enhance efficiency by approximately 40%.
How it Works: AI’s role is crucial in parsing through vast datasets to categorise information, assess risks, and identify viable alternative materials efficiently. The process includes automated literature surveys, multi-level screening, and reviews by various departments, culminating in quality assessments and e-signing. This AI-driven approach significantly speeds up documentation activities and reduces manual effort.
Tech Stack
- Generative AI
- Database management systems
- Analytical tools
Automation in PV Data Intake and Extraction
Tata Elxsi Use Case
Use Case: Leveraging NLP and AI, this approach automates the extraction of information from unstructured sources in pharmacovigilance (PV), enhancing drug and device safety through comprehensive data analysis.
How it Works: Tata Elxsi’s TESafe platform uses AI and NLP engines to identify and process relevant information, while RPA solutions manage documents efficiently. This system ensures data privacy, reduces workforce requirements by up to 30%, and expands case intake sources. AI plays a crucial role in streamlining data management and extraction processes.
Tech Stack
- Natural Language Processing (NLP)
- Robotic Process Automation (RPA)
- AI algorithms
- Data privacy and security tools
Gen AI-based Regulatory Action Impact Analysis
Tata Elxsi Use Case
Use Case: This solution employs Generative AI, web bots, and NLP to analyse the impact of regulatory actions in the life sciences industry, enhancing compliance and product sustainability.
How it Works: By crawling Health Authority (HA) websites and authentic sources, Tata Elxsi’s TEDREG platform provides real-time regulatory updates and automated alerts. Integrated workflows and collaboration networks facilitate swift information sharing, significantly reducing workforce requirements. AI streamlines the assimilation of regulatory updates, enabling effective team collaboration.
Tech Stack
- Generative AI and Natural Language Processing (NLP)
- Web bots for real-time information tracking
- Automated alert systems
- Collaboration and workflow management tools
