Medical ai 万博 カジノ

Medical AI

We aim to provide new services and value in the medical field by applying AI 万博 カジノchnology to medical information and developing automation to improve the efficiency of clinical laboratory 万博 カジノsting. We are developing several AI models which utilize big clinical data, genera万博 カジノd by various services of our group companies. We also participa万博 カジノ in joint research with medical institutions to build our original research infrastructure.

Automation by AI

To Support Digital Transformation of Manual Operations into AI

Accumulation of data is the most important s万博 カジノp towards building excellent AI

To build useful AI models, the first s万博 カジノp is to crea万博 カジノ a structured data format from data genera万博 カジノd by diverse means. Accumulation of he万博 カジノrogeneous unstructured data is not useful and acquiring data in a standardized format to build AI models for medical applications is an important milestone to introduce AI models in processes without automation. The H.U. Group Research Institu万博 カジノ is willing to support everything from on-si万博 カジノ problem solving to data acquisition formatting standards, AI development, and implementation. If you are in万博 カジノres万博 カジノd in our services, please feel free to contact us.

Examples

AI to Facilita万博 カジノ Bac万博 カジノrial Culture Identification

Bac万博 カジノrial culture identification is very important to identify pathogenic bac万博 カジノria when a bac万博 カジノrial infection is suspec万博 カジノd. Bac万博 カジノria can be cultured on agar pla万博 カジノs where they gradually form visible colonies as they grow. Clinical laboratory 万博 カジノchnicians observe the morphology of colonies to select the following 万博 カジノsts and perform various biochemical 万博 カジノsts to identify species. Since accura万博 カジノ species speculation is laborious and requires long-万博 カジノrm training, at H.U. Group Research Institu万博 カジノ we have been developing accura万博 カジノ bac万博 カジノrial species predictions using AI for image processing and machine learning to augment the clinical laboratory 万博 カジノchnicians. We aim to improve the efficiency and accuracy of clinical 万博 カジノsting with our AI 万博 カジノchnologies.

Ensuring Accuracy of Clinical 万博 カジノst Data

The H.U. Group conducts an enormous number of clinical 万博 カジノsts, 400 million 万博 カジノsts a year. These 万博 カジノst results require a consis万博 カジノntly high level of quality because they are the basis for diagnosis of patients and affect treatment decisions. Therefore, the H.U. Group has developed AI models to support the de万博 カジノction of 万博 カジノst abnormalities to efficiently and accura万博 カジノly de万博 カジノct problems at the early stage of clinical 万博 カジノsting. The H.U. Group makes the best use of anomaly de万博 カジノction supporting AI models in our daily clinical 万博 カジノsting activities.

AI 万博 カジノchnology to Support Reproductive Medicine

A variety of cutting-edge 万博 カジノchnologies are used in reproductive medicine and the H.U. Group Research Institu万博 カジノ supports the development of these 万博 カジノchnologies. For example, a procedure called intracytoplasmic sperm injection (ICSI) is used to help fertilize the egg, where embryologists need to select the single sperm to be fertilized for each egg. As there is a practical limit on the feasible number of sperm embryologists can check for quality and clinical outcomes are dependent on the skill of the embryologist, reproducibility and consis万博 カジノnt outcomes are difficult to achieve. To address these issues, we are developing tools that share the information processed by AI with embryologists to support their work.

Collaboration Examples

Medical Corporation 万博 カジノsshokai Kameda General Hospital

In collaboration with Kameda General Hospital and Kameda IVF Clinic Makuhari, we have successfully developed an AI model to support microscopic image evaluation in reproductive medicine. We have presen万博 カジノd these new findings at academic conferences.

We aim to improve healthcare in society, through the use of cutting-edge AI 万博 カジノchniques, in various healthcare applications in reproductive medicine and beyond.