11 results:
SсienceSoft revamped a cloud platform for a company offering remote diagnostic services to healthcare organizations. Alongside code, feature, and UX upgrades, the team boosted the accuracy of a medical image analysis module used for time-sensitive clinical decisions.
ScienceSoft developed a fully customizable, HIPAA-compliant AI voice agent for healthcare scheduling. Built on Amazon Nova Sonic with the first-ever LiveKit Media Server integration, it addresses typical AI agent flaws and aims at a 50% reduction in scheduling costs.
A European medical device manufacturer received a HIPAA- and GDPR-compliant platform to support liver procurement decisions. A predictive model analyzes liver scans from spectrometry devices, estimates steatosis levels, and continuously re-trains to maintain accuracy.
ScienceSoft delivered a compliant web demo of radiographic image analysis software for a global provider of AI-based medical imaging solutions. The demo showcases the SaMD’s capabilities and helps attract potential clients by enabling the product’s free trial.
In 2 months, ScienceSoft provided a US-based biotechnology company with a desktop app for lung cancer detection. The app ensures 100% stable generation of comprehensive diagnostic reports based on analysis of flow cytometry data.
ScienceSoft helped a global provider of AI-powered healthcare imaging solutions introduce a new image generation module and ensure its GDPR, ISO 13485, and IEC 62304 compliance in just three months.
In 6 months, ScienceSoft delivered a ready-to-market MVP of a medical platform for patients with obesity. It comprised cross-platform apps for patients and doctors, integration with HealthKit and Google Fit, and an AI engine for personalized suggestions.
ScienceSoft created a CNN-based application to automatically analyze brain MRI scans, localize tumors, and define each tissue type.
ScienceSoft’s senior data scientist helped deliver an ML-powered software product for automated dental insurance fraud detection. The ISO 13485-compliant medical image recognition algorithms demonstrated 95% accuracy.
Within just 3 months, the Customer received a proof of concept for a machine vision model meant to identify and track single-use sterile surgical supplies. Demonstrating high accuracy, the PoC is ready to be presented to investors.
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