The Inflection Point of AI in Healthcare: A Scan of Domestic and International AI+Healthcare Startup Cases

Artificial intelligence is unleashing a storm of technological innovation. AlphaGo’s decisive victory over Go champion Ke Jie was merely the achievement of a small milestone. Across various fields, AI is expanding its frontiers, disrupting traditions and establishing new rules of the game with novel technologies and strategies.

Artificial intelligence is also making significant strides in the healthcare industry.

AI + Healthcare. Everyone is striving to drive innovation and iteration in future healthcare through their respective fields, topics, projects, and products.

VCBeat has launched an e-book themed “AI + Healthcare,” aiming to summarize the achievements of artificial intelligence in the medical field and drive the healthcare industry chain toward newer and deeper pathways.

2017 was considered the first year of AI applications and a turning point in the development of artificial intelligence.

Robust support from national policies has also provided fertile ground for “AI + Healthcare.” According to data compiled by VCBeat, since 1992, China has issued more than 200 local-level policies and over 80 national-level policies. In 2016 alone, more than 100 AI-related policies were released. This quantitative surge in policy initiatives has driven qualitative advancements in artificial intelligence.

Currently, a complete industrial structure for global AI + healthcare, encompassing “infrastructure + technology + applications,” has basically taken shape. Large corporations are progressively strengthening their layouts in the infrastructure and technology layers, while startups are heavily concentrated in the application layer.

It can be said that in the healthcare sector, artificial intelligence exhibits a higher degree of alignment between R&D and commercialization, accelerates its path to market, and more readily attracts capital investment.

However, every industry has its barriers. Understanding how AI works does not necessarily mean one can successfully harness its applications in the healthcare sector; indeed, there is no shortage of entrepreneurs who have failed in this endeavor.

To help you better understand the broader trends, recognize your competitors, and gain a clear sense of your own position, the VCBeat content and product team has spent three months planning, interviewing, and writing to present this relatively authoritative and comprehensive e-book series on AI + Healthcare.

AI + Healthcare E-Book Series: China Edition

"AI + Healthcare: Domestic Case Studies – Applications in Eight Innovative Fields" e-book provides a comprehensive overview of the application of "AI + Healthcare" in China. Through in-depth interviews within the industry, VCBeat has been pleased to discover that China is developing rapidly in this innovative field, with AI startups emerging to address most segments of the healthcare process.

Table of Contents

01. Medical Imaging Application Cases

02. Virtual Assistant Use Cases

03. Case Studies of Medical Big Data Applications

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DeepCare is a technology company specializing in the recognition and screening of medical images, leveraging artificial intelligence for medical image analysis and early detection. Its distinguishing feature lies in its use of AI technologies. DeepCare focuses on the research and development of technologies for medical image detection, recognition, screening, and analysis. By integrating machine vision, deep learning, and big data mining, the company is committed to providing fast, accurate, and cost-effective medical image recognition solutions to manufacturers of portable medical devices and primary healthcare centers.

DeepCare Homepage

DeepCare’s AI-assisted screening system has achieved diagnostic accuracies of over 90% for cervical cytology smears and over 92.5% for breast cancer lymph node metastasis. Notably, the system’s recognition rate for high-grade squamous intraepithelial lesions (HSIL) in cervical cancer screening exceeds 99%. DeepCare enables partner medical device manufacturers to integrate automated recognition capabilities at a low cost, facilitating the deployment of these devices to township-level primary care clinics. This reduces barriers to adoption and makes chronic disease management more convenient, efficient, and accurate.

Establishing and Operating Cloud-Based Robot Services

Customer Segmentation:Robotics Field

Value Proposition:“Provide every household with a home robot in 2025.”

Core Resources:The world’s first cloud-based intelligent connectivity terminal (AI Mobile), built on dual-chip and virtualization technologies, activates compatible robots through cloud-based artificial intelligence applications.

Key Businesses:Establishing and Operating Cloud-Based Robotic Services

Competitors:GreyOrange, Banggusi Electronic Technology, Blue River Technology

Cumulative Financing and Investment:$130 million

Historical Investors:SoftBank China, Foxconn, Bojiang Capital, Venustech, Zhongguancun Development Group, Shenzhen Capital Group, Walden International, Kaixuan Venture Capital, Zhongke Lechuang, Rongcheng Technology, SoftBank Overseas

Hangzhou Dyingjia Technology Co., Ltd. is a company engaged in software and information consulting services. Its founder is a tenured professor in the United States with 15 years of research experience in digital pathology. The company primarily provides AI-based big data analytics solutions for medical imaging in precision medicine, aiming to address the significant shortage of pathologists in China and facilitate tiered diagnosis and treatment.

AI-assisted diagnostic systems and digital pathology teleconsultation systems can process and analyze whole-slide digital pathology images exceeding 1 GB in size on standard computers within 5–10 seconds, while achieving over 99% accuracy in differentiating between benign and malignant cases for several types of cancer.

Customer Segmentation:Medical Institutions, Physicians

Value Proposition:Your Image Analysis Expert at Your Fingertips

Core Resources:AI-Powered Big Data Analytics Solutions for Medical Imaging in Precision Medicine

Key Businesses:Conduct AI-based analysis and diagnosis of digital pathology slides using deep learning, achieve quantitative cancer analysis, reduce slide reading costs, and improve diagnostic accuracy, providing hospitals with a comprehensive digital pathology solution for remote slide reading and consultation.

Competitors:Butterfly Network, Winning Health, Wanli Cloud

Cumulative Financing and Investment:RMB 15 million

Historical Investors:Jiangmen Ventures

AI + Healthcare E-Book Series: International Edition

European and American countries began developing artificial intelligence at an earlier stage. The e-book "AI + Healthcare Overseas Cases: Applications in Eight Innovative Fields," published by VCBeat, provides a comprehensive overview of the development trends of artificial intelligence abroad through chapters covering hospital process management, smart hardware applications, medical imaging diagnosis, new drug tracking, health monitoring, and disease risk prediction.

Table of Contents

01. Hospital Management Application Cases

02. Smart Hardware Application Cases

03. Application Cases of Medical Imaging Diagnosis

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Qventus, formerly known as AnalyticsMD, is a startup that provides intelligent decision-support analytics systems for hospitals. Founded in 2013 and headquartered in Palo Alto, California, the company was co-founded by Mudit Garg, Brent Newhouse, and Ian Christopher. The team brings extensive experience in healthcare and big data processing. Qventus’s algorithms analyze hospital data based on clinical metrics, and its machine learning–powered predictive technology can forecast patient volumes and provide recommendations for optimizing resources, such as staffing, beds, and rooms.

DecisionOS, developed by AnalyticsMD, extracts big data from hospitals’ own EMR systems (compatible with most mainstream hospital EMR systems, with encrypted data ensuring HIPAA compliance). Through machine learning algorithms, the system automatically analyzes, monitors, and forecasts, providing clinicians with the most appropriate recommendations to help them deliver optimal treatment and care to patients in a timely manner. Physicians no longer need to spend excessive time reviewing complex case reports and other data. As a result, patient safety, satisfaction, and healthcare cost control are effectively addressed.

Qventus Product Solutions

Through large-scale machine learning predictions, analyzed metrics such as patient length of stay and patient volume are visualized to provide healthcare professionals with enhanced decision support. By analyzing hospital-specific service data, underlying causes of issues such as insufficient ward or operating room capacity can be identified, thereby helping administrators optimize hospital resource allocation.

Customer Segmentation: Healthcare Institutions

Value Proposition: Improve hospital efficiency, patient experience, and clinician satisfaction.

Key Business: Hospital Virtual "Air Traffic Control" to Improve Operational Efficiency.

Core Resources: Transform data into action, establish a logical hierarchy, break down silos between departments, and help hospitals respond to an ever-changing environment.

Competitors：welltok、Qualaris Healthcare Solutions、Amara Health Analytics 、RightCare Solutions

Cumulative Investment and Financing: Cumulative funding of $13.8MHistorical Investors: Mayfield Fund, Norwest Venture Partners, StartX, Y Combinator, Fenox Venture Capital

BioBeats transforms vital signs into personalized music, enabling users to meditate, run, or combat illness through sound. By interpreting biometric data, BioBeats helps users adapt to more engaging and healthier lifestyles. The company leverages machine learning technologies to assist users in managing their health and reducing stress.

Customer Segmentation: General public, enterprise users

Value Proposition: Help manage your health and productivity.

Core Resources: Biometric and psychometric feedback, combined with proprietary machine learning algorithms, delivers personalized stress and productivity management tools grounded in clinical coaching techniques.

Key Business: Corporate and Personal Health Solutions

Competitors：PhysIQ、Scanadu Scout

Cumulative Financing and Investment：$3.23M

Historical Investors： Plug and Play Accelerator、AXA Strategic Ventures、IQ Capital Partners、White Cloud Capital

Zebra Medical Vision is building a medical imaging insights platform. The company offers a cloud-based, fully managed development environment that provides large-scale structured datasets, data storage, GPU computing, and support for various research tools. The solution also enables research teams to collaborate and establish co-working spaces.

Customer Segmentation: Medical Institutions

Value Proposition: To provide automated, accurate, and timely medical image diagnosis for humanity.

Core Resources: One of the largest anonymized databases of medical imaging and clinical data

Key Business: Imaging analysis of the skeletal system, liver, lungs, brain, and cardiovascular system

Competitors: Imagen Technologies, Enlitic, IBM Watson, Arterys

Partners: NVIDIA, Tel Aviv University

Cumulative Financing: $20M

Historical Investors:
NVIDIA GPU Ventures 
Deep Fork Capital 
Dolby Family Ventures 
Intermountain Healthcare 
Khosla Ventures

We hope these innovative companies, deeply rooted in artificial intelligence, will inspire you. In the future, the convergence of AI and healthcare holds even more opportunities, awaiting those with the insight to uncover them.