HEALTHCARE & LIFE SCIENCES
Developing AI-Based Diagnostic & Patient Solutions
Overview
Healthcare and life sciences organizations have increasingly moved towards AI and data science solutions as they strive to innovate and improve patient care in a fast-paced, competitive, and highly regulated environment. SFL Scientific leverages our team of Ph.D. and Data Science experts to help you build robust products based on strong clinical data.
We work with leading organizations












CAPABILITIES
Top Healthcare and Life Sciences AI Solutions
Data Science and AI have the ability to transform healthcare and life science institutions and start-ups. Capitalize on the advances being made to solve problems and enhance current healthcare modalities that improve patient care while reducing overhead costs.
Medical Imaging & Diagnostic Tools
- Deep Learning for Radiology/Pathology
- Disease & Anomaly Detection
- Simulation & Surgical Applications
- Virtual & Consumer Applications
Patient Insights & NLP
- Precision Medicine, Biomarkers
- EMR & Records Mining
- Segmentation & Risk Monitoring
- Population Health & Journey
Medical Devices/IOT
- Wearables & Remote Medicine
- Event Triage & Monitoring
- Predictive Health & Maintenance
- Intelligent Diagnostic Systems
Organization Optimization
- Fraud & Compliance
- Supply Chain & Inventory
- AI For Call Center / Triage
- Claims & Document Management
USE CASES
Advancing R&D & AI Solutions
The value of data is realized only when stakeholders buy-in into the diverse set of technologies emerging at the provider, payer, and patient level. Enabling data-driven insights and practical AI opportunities for healthcare organizations to deliver ground-breaking medicine and patient care requires expert data scientists.
Predicting Multiple Sclerosis Transition with Machine Learning
Working with the Accelerated Cure Project for Multiple Sclerosis, a non-profit organization whose mission is to accelerate research efforts to improve diagnosis and treatment for multiple sclerosis (MS), our goal was to develop a set of machine learning models to predict MS disease evolution and determine crucial transitions in MS progression.

Remote Medicine Using Audio Data
SFL Scientific developed a supervised learning algorithm from audio data to detect sleep apnea using features in audio data from mobile devices set next to the bedside at night.

The ability to couple large medical imaging datasets from our leading healthcare partners with the exceptional computational performance of the NVIDIA V100 GPUs and novel deep learning model development from SFL Scientific have been critical in building our portfolio of AI image classifier applications.
Jim Havelka, InformAI Founder & CEO
SFL Scientific exceeded our expectations in terms of time to results, collaboration, and data science expertise. Partnering with SFL increased our understanding of the potential for using AI with health data to provide people affected by MS and their healthcare providers with predictive information about the progression and transitions of the disease.
Robert McBurney, PhD, Chief Research Officer
People Powered from Data Management to Custom Solutions and Deployment
Healthcare and Life science companies and institutions know it’s not a question of whether or not to deploy AI solutions, but a matter of when and where to start.
Our US-based team of data scientists, consultants, and engineers can guide you through the process of driving real business value with AI. We will work to understand your AI business cases, identifying unique areas of innovation that require further research with proof of concept through building models and deploying sustainable, performant AI business applications at scale.

Our Custom Strategy
Computer Vision
Performance monitoring (predictive analysis, time-series, machine vision)
Learn MoreData Engineering
Designing data architecture and best practices for secure, efficient, and cost-effective data and IT systems.
Learn MoreWORK WITH US
Start a Project
We’d like to work with you to understand your unique AI challenge from modernizing legacy platforms to developing new AI solutions. Technology moves fast, let’s build sustainable solutions.