Staying ahead of the technology curve means strengthening your competitive advantage. That is why we give you data-driven innovation insights into the healthcare industry. This time, you get to discover five hand-picked machine learning startups impacting healthcare diagnostics.
Out of 359, the Global Startup Heat Map highlights 5 Top Machine Learning Startups impacting Healthcare Diagnostics
The insights of this data-driven analysis are derived from the Big Data & Artificial Intelligence (AI)-powered StartUs Insights Discovery Platform, covering 2 093 000+ startups & scaleups globally. The platform gives you an exhaustive overview of emerging technologies & relevant startups within a specific field in just a few clicks.
The Global Startup Heat Map below reveals the distribution of the 359 exemplary startups & scaleups we analyzed for this research. Further, it highlights five HealthTech startups that we hand-picked based on criteria such as founding year, location, funding raised, and more. You get to explore the solutions of these five startups & scaleups in this report. For insights on the other 354 machine learning solutions for healthcare diagnostics, get in touch with us.
Avicenna simplifies Medical Image Analysis
Founding Year: 2018
Location: La Ciotat, France
Funding: USD 3,53 M
Reach out for Real-Time Triaging
French startup Avicenna offers medical image analysis for neurovascular and thoracoabdominal triage. The startup’s solution uses deep learning to analyze computed tomography (CT) images of the head and chest. It enables rapid disease detection, reduces radiologist data overload and stress, as well as decreases misdiagnosis. Consequently, it improves patient management, ensures prompt therapeutic response, and, in turn, enhances patient outcomes.
Medipixel facilitates Coronary Artery Analysis
Founding Year: 2017
Location: Seoul, South Korea
Funding: USD 8,6 M
Partner for Automated Angiogram Classification
South Korean startup Medipixel offers a machine learning-based solution for coronary artery analysis. The startup’s solution, Medipixel XA, combines computer vision, deep learning, and reinforcement learning to analyze coronary angiograms. It provides automated angiogram classification, lesion analysis, automated vessel segmentation, and stent recommendation. This mitigates the need for error-prone manual segmentation, saving time in disease diagnosis. Medipixel reduces treatment times for hospitals, radiation exposure for doctors, and treatment costs for patients.
OrthoPred offers Radiology Reporting Automation
Founding Year: 2017
Location: Győr, Hungary
Funding: USD 537 000
Innovate with OrthoPred for Knee Anatomy Analysis
Hungarian startup OrthoPred provides radiology reporting automation. The startup’s platform, DeepKnee, leverages deep learning to automatically annotate knee MRI scans as well as to detect and localize meniscus and ligament tears. It integrates with clinical workflows to automate magnetic resonance imaging (MRI) analysis. This way, it acts as a data-driven decision support system for clinicians to speed up bone tear diagnostics.
Imsight Technology develops a Cell Screening System
Founding Year: 2017
Location: Hong Kong
Funding: USD 27,7 M
Use this solution for Oncology Decision Support
Hong Kong-based startup Imsight Technology builds a cervical liquid-based cell screening system. The startup’s solution, Cervical-Sight, utilizes convolutional neural networks for automated cytopathic image analysis. It identifies up to 15 types of abnormalities and provides whole slide screening to reduce diagnosis errors, improving screening efficiency. Another solution, Cervix-Pilot, accurately delineates target areas and organs at risk. The startup’s solutions standardize target delineation workflow and provide decision support for cervical cancer diagnosis.
Xylexa facilitates Breast Cancer Diagnostics
Founding Year: 2017
Location: Islamabad, Pakistan
Work with Xylexa for Mammogram Analysis
Pakistani startup Xylexa develops a computer-aided diagnostics (CADx) platform for the detection of breast cancer. The platform uses deep learning-based image processing to analyze mammogram scans. This enables healthcare providers to accurately diagnose breast cancer at early stages and reduce image reading time, decreasing recall rate. It also lowers false positives and prevents unwanted follow-ups and biopsies, allowing radiologists to reduce incorrect or late diagnosis.
Discover more Healthcare Startups
Healthcare startups such as the examples highlighted in this report focus on medical report analysis, vitals monitoring, and clinical decision support. While all of these technologies play a major role in advancing the healthcare industry, they only represent the tip of the iceberg. To explore healthcare technologies in more detail, simply let us look into your areas of interest. For a more general overview, download our free Healthcare Innovation Report to save your time and improve strategic decision-making.
