According to the World Health Organization report, cancer is the leading cause of death worldwide, with lung cancer, liver cancer and stomach cancer being the three most common types of cancer. In 2008, 7.6 million people died of cancer (about 13% of all deaths), and it is expected that by 2030, the number of cancer deaths worldwide will continue to rise to more than 13.1 million.
In fact, many cancers can be prevented by controlling risk factors that can be changed, such as unhealthy eating habits (smoking, drinking, etc.), work habits, and too little exercise. In addition, if early can be found, a significant proportion of cancer can be cured by surgery, radiation or chemotherapy.
However, cancer is a progressive disease, from gestation to outbreaks, ranging from a few years to more than a decade or even decades. It starts slowly and quickly after the outbreak. There are almost no symptoms in the early days. Most people There is no habit of regular physical examination, and there are already symptoms that can be perceived before going to the hospital for examination. At this time, the cancer diagnosis results are basically in the middle and late stages.
With the rapid development of artificial intelligence in the medical field, it is inevitable to apply it to the processing of heavy medical data. In this ever-changing entrepreneurial ecosystem, more and more companies hope to help doctors diagnose cancer. Make a bigger breakthrough, Predible Health is one of them.
Combine the power of deep learning and cloud computing to analyze medical images, providing radiologists with personalized access to personalized treatment solutions (accessible directly via a web browser).
Predible is a startup in India and was founded in May 2016 by the Indian Institute of Technology's Suthhirth Vaidya, Abhijith Chunduru and Deepak Mohan. The company can help radiologists analyze medical scan files and diagnose cancer, and it can also diagnose liver cancer and lung cancer through its supported artificial intelligence cloud software.
Predible said that they "can interpret medical scan images with greater precision and speed."
Predible products
Predible has developed two flagship products, PREDIBLE LIVER and PREDIBLE LUNG.
PREDIBLE LIVER: This product was developed in collaboration with radiologists, HPB (health bureau) and transplant surgeons.
PREDIBLE LIVER helps surgeons with accurate planning of liver transplants and tumor resections through real-time analysis and 3D visualization of liver damage and liver structure. Hospitals across India can connect PREDIBLE LIVER via the Internet to obtain analytical results, assist them in planning surgery, and reduce post-recurrence rates.
Press the Analysis button to automatically perform automatic liver segmentation and liver injury description, provide surgical planning and effect evaluation
1) Description of Liver Damage - Use a sophisticated algorithm to segment the liver and accurately detect and describe all liver lesions and liver damage in a simple workflow.
2) Provide a surgical plan - use automatic segmentation and 3D interactive tools (such as virtual resection) for liver capacity measurements.
3) Effect evaluation - The mRECIST (solid tumor efficacy evaluation standard) protocol is used to quantitatively track the tumor's viability, which is convenient for making more accurate treatment recommendations.
PREDIBLE LUNG: This product was developed in collaboration with radiologists and oncologists.
Automated malignancy score, nodule tracking, and effect evaluation by pressing the Analysis button
1) Malignant tumor score - non-invasive diagnosis with the help of malignant tumor detection and lung cancer CT image risk score.
2) Nodulation tracking - Nodule tracking according to standard protocols, screening for lung cancer in high-risk patients with lung cancer.
3) Evaluate the effect - make a better evaluation of the therapeutic effect by longitudinal and quantitative tracking of the nodulation.
The rapid clinical explanation of liver cancer and lung cancer through artificial intelligence enables radiologists to understand image data more quickly and accurately, and promotes the diagnosis process of cancer. Predible said that since the launch of PREDIBLE LIVER and PREDIBLE LUNG in 2016, more than 2 million images have been processed. It is planned to process 500 million sheets by December 2020, and the accuracy of the products will be continuously improved during the processing. Currently, Predible is working with medical institutions such as Mumbai Tata Memorial Hospital, Mahajan Imaging in Delhi and Narayana Health in Bangalore.
Predible Patient Privacy Policy
When the user (doctor or patient) uses the Predible service, personal basic information such as name, age, contact information, and medical information such as image data, such as image data, will be provided. These personal data will only be collected and processed, Predible will be proper. In the custody, the user's personal data will not be transferred to a third party for any other purpose unless it is licensed.
The user sends the data to be analyzed to Predible, and Predible will only use the data to perform the analysis items it requires, and store and send the analysis results to the user. In addition, the user has access to the storage of any data about himself, and there is also the right to ask Predible to correct or delete some of the data.
Predible has a network team dedicated to protecting user information, regularly testing various vulnerabilities, handling unauthorized access, and preventing hackers and other intrusion systems from stealing user privacy. With the advancement of technology, Predible's security measures are constantly improving.
Predible announces completion of pre-A round of financing
Predible Health announced that it completed the pre-A round of financing on March 2, 2018. The specific amount of financing was not disclosed. The investor was the Unitus Seed Fund focused on seed stage investment. According to Sririkishna Ramamoorthy, a venture capital partner at Unitus Seed Fund, the amount of this round of financing may be between 2,000 and 25 million rupees (about 30-400,000 US dollars). Predible said it plans to use this latest financing to increase the development of its artificial intelligence platform and launch more new products.
Unitus's Milind Shah commented on Predible's more than a year of development: "Predible has built an artificial intelligence cancer radiology platform in a short period of time to help radiologists and surgeons accurately and quickly diagnose diseased tissue and determine the size of cancer tissue. This will not only greatly improve the efficiency of the radiologist, but also achieve clinical results that reduce patient mortality."
In addition to Predible, the startup dedicated to cancer treatment is also based in Bangalore's OncoStem Diagnostics, which was founded in 2011 to focus on developing algorithms that predict the probability of cancer recurrence in patients, testing patients, and developing Personalized cancer treatment program. Others include cancer treatment startups supported by Ratan tata, Invictus Oncology, Celon Labs, and iGenetics Diagnostics.
The development of AI technology in the medical field has become more and more fierce in recent years, and the competition of various companies lies in the competition of technology. "In order to enhance Predible's competitiveness in the market, we will use Unitus' investment to further expand the company's cancer diagnostic artificial intelligence platform. Of course, we will also intercept some funds for regulatory approval of existing products," said Predible's chief Executive Officer Suthirth Vaidya said: "The clinical validation studies we have conducted have shown positive results, and we are currently working to incorporate products into clinical practice."
In addition to commercial product development, Predible also hopes to work with more leading healthcare organizations to promote deep learning technology in cancer detection and treatment, providing more efficient and accurate healthcare for developing countries such as India. solution.
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