Development of an AI-based support system for controlled ovarian stimulation.

Purpose: Controlled ovarian stimulation (COS) is vital for IVF. We have developed an AI system to support the implementation of COS protocols in our clinical group.

Methods: We developed two models as AI algorithms of the AI system.

Retardation of freezing of precooled, impinged water droplets on glass surfaces with microgrooves and silane coating.

Freezing impinged water droplets on glass surfaces cause serious problems such as reduced visibility of traffic lights and surveillance cameras. Droplets in the air associated with these issues are often at subzero temperatures. However, experimental results on the freezing of precooled impinged droplets are limited.

Deep convolutional neural network-based algorithm for muscle biopsy diagnosis.

Histopathologic evaluation of muscle biopsy samples is essential for classifying and diagnosing muscle diseases. However, the numbers of experienced specialists and pathologists are limited. Although new technologies such as artificial intelligence are expected to improve medical reach, their use with rare diseases, such as muscle diseases, is challenging because of the limited availability of training datasets.

Deep learning shows the capability of high-level computer-aided diagnosis in malignant lymphoma.

A pathological evaluation is one of the most important methods for the diagnosis of malignant lymphoma. A standardized diagnosis is occasionally difficult to achieve even by experienced hematopathologists. Therefore, established procedures including a computer-aided diagnosis are desired.