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 5 hand-picked deep learning startups.
Out of 417, the Global Startup Heat Map highlights 5 Top Deep Learning Startups impacting Healthcare
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 417 exemplary startups & scaleups we analyzed for this research. Further, it highlights 5 healthcare 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 5 startups & scaleups in this report. For insights on the other 412 deep learning solutions for healthcare, get in touch.
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Teton.ai facilitates Patient Monitoring
Founding Year: 2020
Location: Copenhagen, Denmark
Funding: USD 1,26 M
Partner for: Hospital Workflow Management
Teton.ai is a Danish startup that provides Nightingale, a patient monitoring and workflow management platform for hospitals. The startup combines computer vision and deep learning to analyze body position, measure activity level, and calculate respiration rate, among others. This contactless solution enables nurses to continuously monitor patient conditions and prevent adverse events. Nightingale allows healthcare staff to track the development and behavior of neurological patients to detect subtle signals and mitigate accidents that may lead to injuries.
Medmain enables Remote Pathological Diagnosis
Founding Year: 2018
Location: Fukuoka, Japan
Funding: USD 10 M
Partner for: AI-based Image Screening
Japanese startup Medmain offers PidPort, a high-precision, remote pathological analytics system. PidPort combines deep learning and cloud computing to accelerate and improve pathological image diagnosis. Since the service is cloud-based, various medical practitioners are able to simultaneously collaborate to minimize diagnosis errors. For hospitals, PidPort simplifies the storage and management of pathological image data, ensures data compliance, and reduces data storage costs.
Visionairy Health offers Triage Optimization
Founding Year: 2017
Location: Boston, USA
Funding: USD 100 000
Partner for: Prioritization of Chest X-rays
Visionairy Health is a US-based startup that develops software for triage optimization. The startup’s X1 is an AI-based software that offers triage and prioritization of chest X-rays. The software uses deep learning to analyze chest x-rays, and flags images with concerning anomalies. It is a picture archiving and communication system (PACS)-agnostic tool that also integrates with existing radiology software. This allows medical practitioners to minimize diagnostic errors and assists doctors in decision-making.
DiagnostiX enables Cardiovascular Diagnostics
Founding Year: 2019
Location: Geneva, Switzerland
Partner for: Cardiovascular Disease Detection
Swiss startup DiagnostiX develops CV-AI, a decision-support tool for cardiovascular diagnosis. The startup applies neural networks and AI to brain scan data and generates preventive risk models for stroke prevention. These models support additional variables such as lifestyle, stress factors, and potential environmental changes. CV-AI assists physicians in patient diagnosis as well as in providing treatment suggestions based on the probability of success. This strengthens decision-making and offers patients the ability to choose treatments that increase the chance of successful treatment outcomes.
Hanalytics detects Neurological Diseases
Founding Year: 2017
Location: Singapore
Partner for: Neuroimaging Analysis
Singaporean startup Hanalytics develops BioMind, a neuroimaging analysis application for disease diagnostics and detection. BioMind utilizes deep learning and NLP to analyze magnetic resonance imaging (MRI) or computed tomography (CT) scans to facilitate patient diagnosis and treatment. The startup’s solution offers decision support for brain tumors, cerebrovascular diseases, hemorrhage, and pneumonia. This enables physicians to improve patient care and rely on data-driven disease diagnoses.
Discover more Healthcare Startups
Healthcare startups such as the examples highlighted in this report focus on deep learning tools for patient monitoring, clinical decision support systems, and neurological devices. While all of these technologies play a major role in advancing the healthcare industry, they only represent the tip of the iceberg. To explore more healthcare technologies, simply get in touch to let us look into your areas of interest. For a more general overview, you can download our free Healthcare Innovation Report to save your time and improve strategic decision-making.
