Kyoto, April 19, 2017

Hacarus today announced the launch of data analysis service to enterprise customers by incorporating the sparse modeling technology that enables extraction of the most relevant piece of information from very small data set.


The service is realized by adopting the company’s existing technology and software assets used in the health management app ‘Hacarus’ to general data analysis purposes, and makes it possible to fully-automate computer based data analysis and recognition in an environment where large amount of data required for deep learning cannot be obtained.


1. Background


Hacarus has been developing the health management app that incorporates sparse modeling technology since June 2016 jointly with a professor Masayuki Ohzeki of Tohoku University who is also Chief Science Advisor at Hacarus, and offering the health management service to enterprise customers as well as fitness clubs through its mobile app.


By leveraging the characteristics of sparse modeling that can extract the most relevant piece of information from very small data set, Hacarus established a new method of analyzing and identifying the user’s health condition even with a partial vital data (aka a sparse data) and greatly reduced the amount of data input required by users which is often referred as the biggest challenge of healthcare services.


On the other hand, Hacarus has been hearing from enterprise customers having difficulty applying deep learning to computer based analysis and recognition where they cannot obtain enough amount of training data. Hacarus’ data analysis service is introduced in order to solve this problem by applying the company software assets related to sparse modeling technology originally developed for healthcare to general data analysis.


From left: Masayuki Ohzeki (Professor at Tohoku University), Kenshin Fujiwara (CEO at Hacarus, earned Computer Science degree at California State University), Takashi Someda (CTO at Hacarus, earned Informatics System degree at Kyoto Univeristy)


2. Sparse Modeling Use Case


The method of intentionally reducing the amount of data and reconstructing the original data from it is often called compressive sensing. Below is an example of reconstructing the original image data by applying sparse modeling technology from the image data collected by shortening the scanning time of MRI by a quarter.


This not only obtains the desired image data necessary for diagnosis while minimizing the burden on the patient but also improves economics of MRI, which is an expensive medical device, by shortening the scanning time it takes each. The sparse modeling in compressive sensing is being applied to medical devices other than MRI these days.


Example of cerebral blood vessel image: compressive sensing can reconstruct blood vessel image even if 80% data is missing. Source: ZDNet Japan


3. Hacarus Data Analysis Use Cases


Hacarus will provide the service targeting various data initially focusing on analysis and recognition of image data, which is one of the main applications of sparse modeling technology.


In addition, Hacarus will also provide the service that can identify the correlation between data, which is another characteristic of sparse modeling. This enables finding of “correct training data” where deep learning is not designed for. This is realized by analyzing and identifying what is characterizing output data for input data by leveraging the uniqueness that sparse modeling technology is excellent in extracting the relevant piece of information from given data.


Below is an example of using Hacarus data analysis service.


– Reconstruction of medical images by compressive sensing

– Identification of disease type using appearance images of plants and people

– Identification of damaged parts from photographs taken by drone

– Identification of affecting factors in KPIs from large amount of business data

– Investigation of correlation between various vital data and illness risk / medical expenses


At the moment, Hacarus will provide the service as a contract work to create a model that captures the characteristics of given data, but in future Hacarus will provide the analysis services corresponding to specific data types as APIs. By using these APIs, enterprise customers can easily incorporate sparse modeling technology into existing systems.


4. Getting Quote


Please contact for quote.


5. About Hacarus


Headquarters: Kikusan Bldg. 3F Room 302 112 Machigashiracho Nakagyo-ku, Kyoto-shi Kyoto 604-8206 Japan

Established: January 14, 2014

Capital: 22,450,000 JPY

Investors: Miyako Capital, Chushin Venture Capital, Senshu Ikeda Capital, Kyogin Lease Capital, Board Members



[ Inquiry about this press release ]

Tel: +81-75-708-5516 / Email:


Hacarus Inc. (Headquarters: Kyoto Japan, CEO: Kenshin Fujiwara) today announced that the company appointed Masayuki Ohzeki of the Graduate School of Informatics, Kyoto University as the company’s Chief Science Advisor.


1. Overview


As of May 25, 2016 Masayuki Ohzeki of the Graduate School of Informatics, Kyoto University was appointed as the company’s Chief Science Advisor. Mr. Ohzeki is a researcher and award winner of the 2016 Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology. With his expertise in machine learning algorithm using sparse modeling, the company develops the differentiated mobile healthcare service under his supervision.


Sparse modeling is a new methodology to extract the most relevant piece of information from the large amount of data. By applying this methodology to the large vital data Hacarus owns, a doctor and nutritionist are able to reduce the number of items in vital data they need to reference, which makes it possible for the company to provide a health management service to its customers more efficiently. In addition, sparse modeling has a competitive advantage over deep learning that heavily relies on the massive computing resources, and hence it is suitable for affordable and consumer oriented services.


By incorporating this sparse modeling based machine learning system as technical seed, the company develops the system jointly with Kyoto University under Mr. Ohzeki’s supervision, that can extract the most relevant information to user’s health condition from the large vital data.


2. Advisor Profile


Masayuki Ohzeki:

March 2004, Bachelor of Science, Tokyo Institute of Technology.

March 2006, Master of Science, Tokyo Institute of Technology.

September 2008, Doctor of Science, Tokyo Institute of Technology.

October 2008, Post-Doctoral Fellow, Tokyo Institute of Technology.

May 2010, Assistant Professor, Adaptive Systems Theory, Department of Systems Science, Graduate School of Informatics, Kyoto University.


3. About Hacarus


Hacarus is a healthcare startup based in Kyoto Japan providing weight loss and low carb diet programs via mobile app. The company is founded in 2014 by the former Sony PlayStation engineer. CEO has co-founded several tech startups with 2 exits in the past 15 years, bringing lots of technical knowledge and entrepreneurial mindset to the company.

Company Name: Hacarus Inc.
Address: Kyoto Research Park Bldg. #6 Room 406 93 Chudoji Awata-cho Shimogyo-ku, Kyoto-shi, Kyoto, 600-8815 Japan
CEO: Kenshin Fujiwara
Founded: January 14, 2014


Contact info

Tel: +81-75-925-9111 Attn: Kawakami