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AI IN HEALTHCARE PREDICTING BATTERY LIFE FOR MEDICAL DEVICES

Built a medical equipmentu2019s battery<br>remaining life prediction system leveraging<br>Machine Learning models based on early life<br>cycle test data. The model predicted the<br>remaining life in terms of the number of<br>cycles

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AI IN HEALTHCARE PREDICTING BATTERY LIFE FOR MEDICAL DEVICES

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  1. Built a medical equipment’s battery remaining life prediction system leveraging Machine Learning models based on early life cycle test data. The model predicted the remaining life in terms of the number of cycles.

  2. A global leader in medical technology, the customer provides cutting- edge solutions in Medical & Surgical, Neurotechnology, Orthopaedics, and Spine to enhance patient outcomes. With a commitment to innovation, they develop advanced medical products and services that empower healthcare professionals, improve treatments, and drive better clinical results worldwide.

  3. ThirdEye developed a Machine Learning model trained on early life cycle test data, predicting remaining battery life with up to 90% accuracy, enabling proactive decision-making. Utilizing advanced regression models, reinforcement learning, and active learning techniques, the solution continuously improves accuracy, optimizing battery performance in critical medical devices.

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