The recent progress of computing, machine learning, and especially deep learning, for image recognition brings a meaningful effect for automatic detection of various diseases from chest X-ray images (CXRs). Here efficiency of lung segmentation and bone shadow exclusion techniques is demonstrated for analysis of 2D CXRs by deep learning approach to help radiologists identify suspicious lesions and nodules in lung cancer patients. Training and validation was performed on the original JSRT dataset (dataset #01), BSE-JSRT dataset, i.e. the same JSRT dataset, but without clavicle and rib shadows (dataset #02), original JSRT dataset after segmentation (dataset #03), and BSE-JSRT dataset after segmentation (dataset #04). The results demonstrate the high efficiency and usefulness of the considered pre-processing techniques in the simplified configuration even. The pre-processed dataset without bones (dataset #02) demonstrates the much better accuracy and loss results in comparison to the other pre-processed datasets after lung segmentation (datasets #02 and #03).

Abstract:With the rapid development of assisted reproductive technology, various reproductive disorders have been effectively addressed. Acupuncture-like therapies, including electroacupuncture (EA) and transcutaneous electrical acupoint stimulation (TEAS), become more popular world-wide. Increasing evidence has demonstrated that EA and TEAS are effective in treating gynecological disorders, especially infertility. This present paper describes how to select acupoints for the treatment of infertility from the view of theories of traditional Chinese medicine and how to determine critical parameters of electric pulses of EA/TEAS based on results from animal and clinical studies. It summarizes the principles of clinical application of EA/TEAS in treating various kinds of reproductive disorders, such as polycystic ovary syndrome (PCOS), pain induced by oocyte retrieval, diminished ovarian reserve, embryo transfer, and oligospermia/ asthenospermia. The possible underlying mechanisms mediating the therapeutic effects of EA/TEAS in reproductive medicine are also examined.

No abstract

Acute phase proteins and inflammatory cytokines (IL-1β, IL-6, and TNF-α) show significant changes between the AMS group and the non-AMS group. Combination of inflammatory cytokines or acute phase proteins improves the specificity for diagnosis of AMS. This might provide objective indexes for scanning and screening individuals susceptible to AMS in the early stage of rapid ascending.

No abstract