Finding Nursing in the Room from Accelerometers and Audio on Mobile Sensors

In this paper, we propose a method for finding intervals of nursing activities from accelerometers and audio on mobile sensors which are attached to nurses in reality. If we can find the intervals of nursing activities correctly, it helps the data to be used for machine learning for activity recognition. We have extracted the times of nursing interactions between nurses and patients by A) recognize walking activity from accelerometers, B) recognize if s/he is in the patient’s room or not at each time duration divided by walking activities, from the environmental noise levels of sounds, and, C) for the du- ration where s/he is assumed to be in the patient’s room, apply voice activity detection by fundamental frequencies using Cepstrum method, and extract the duration in which a person speaks. As a result of the experience for 300sec of sensor data, we observed sufficient accuracy for each step of A)-C), and could reduce the time to 8%.Third International Workshop on Location Awareness for Mixed and Dual Reality (LAMDa’13), In Conjunction with the International Conference on Intelligent User Interfaces (IUI’13), March 19th, 2013, Santa Monica, California, US

Clinical epidemiology and pharmacoepidemiology studies with real-world databases

Hospital-based registry data, including patients’ information collected by academic societies or government based research groups, were previously used for clinical research in Japan. Now, real-world data routinely obtained in healthcare settings are being used in clinical epidemiology and pharmacoepidemiology. Real-world data include a database of claims originating from health insurance associations for reimbursement of medical fees, diagnosis procedure combinations databases for acute inpatient care in hospitals, a drug prescription database, and electronic medical records, including patients’ medical information obtained by doctors, derived from electronic records of hospitals. In the past ten years, much evidence of clinical epidemiology and pharmacoepidemiology studies using real-world data has been accumulated. The purpose of this review was to introduce clinical epidemiology and pharmacoepidemiology approaches and studies using real-world data in Japan

Surgical Management of Malignant Tumors of the Trachea: Report of Two Cases and Review of Literature

Malignant neoplasms occurring from the trachea are extremely rare. Therefore, their clinical characteristics and surgical results have not been thoroughly discussed. These tumors are often misdiagnosed and treated as bronchial asthma or chronic obstructive pulmonary disease. It is critically important to probe the cause-effect relationship between the medical presentations and the clinical diagnosis. In this report, two cases of tracheal malignancy suffering from dyspnea due to obstruction of the proximal trachea are described, and a review of the literature is presented

Bactericidal Effects of Diode Laser Irradiation on Enterococcus faecalis Using Periapical Lesion Defect Model

Objective. Photodynamic therapy has been expanded for use in endodontic treatment. The aim of this study was to investigate the antimicrobial effects of diode laser irradiation on endodontic pathogens in periapical lesions using an in vitro apical lesion model. Study Design. Enterococcus faecalis in 0.5% semisolid agar with a photosensitizer was injected into apical lesion area of in vitro apical lesion model. The direct effects of irradiation with a diode laser as well as heat produced by irradiation on the viability of microorganisms in the lesions were analyzed. Results. The viability of E. faecalis was significantly reduced by the combination of a photosensitizer and laser irradiation. The temperature caused by irradiation rose, however, there were no cytotoxic effects of heat on the viability of E. faecalis. Conclusion. Our results suggest that utilization of a diode laser in combination with a photosensitizer may be useful for clinical treatment of periapical lesions

Application of the symbolic regression program AI-Feynman to psychology

The discovery of hidden laws in data is the core challenge in many fields, from the natural sciences to the social sciences. However, this task has historically relied on human intuition and experience in many areas, including psychology. Therefore, discovering laws using artificial intelligence (AI) has two significant advantages. First, it makes it possible to detect laws that humans cannot discover. Second, it will help construct more accurate theories. An AI called AI-Feynman was released in a very different field, and it performed impressively. Although AI-Feynman was initially designed to discover laws in physics, it can also work well in psychology. This research aims to examine whether AI-Feynman can be a new data analysis method for inter-temporal choice experiments by testing whether it can discover the hyperbolic discount model as a discount function. An inter-temporal choice experiment was conducted to accomplish these objectives, and the data were input into AI-Feynman. As a result, seven discount function candidates were proposed by AI-Feynman. One candidate was the hyperbolic discount model, which is currently considered the most accurate. The three functions of the root-mean-squared errors were superior to the hyperbolic discount model. Moreover, one of the three candidates was more “hyperbolic” than the standard hyperbolic discount function. These results indicate two things. One is that AI-Feynman can be a new data analysis method for inter-temporal choice experiments. The other is that AI-Feynman can discover discount functions that humans cannot find

A Case of Subhyoidal Median Ectopic Thyroid Associated with Lingual Thyroid

A case of subhyoidal median ectopic thyroid associated with lingual thyroid was observed in a 14-year-old girl. The subhyoidal median ectopic thyroid was excised for cosmetic reason. The postoperative course has been satisfactory without hypertrophy of the lingual thyroid due to periodic administration of triiodothyronine

Effect of Saxagliptin on Endothelial Function in Patients with Type 2 Diabetes : A Prospective Multicenter Study

The dipeptidyl peptidase-4 inhibitor saxagliptin is a widely used antihyperglycemic agent in patients with type 2 diabetes. The purpose of this study was to evaluate the effects of saxagliptin on endothelial function in patients with type 2 diabetes. This was a prospective, multicenter, interventional study. A total of 34 patients with type 2 diabetes were enrolled at four university hospitals in Japan. Treatment of patients was initially started with saxagliptin at a dose of 5 mg daily. Assessment of endothelial function assessed by flow-mediated vasodilation (FMD) and measurement of stromal cell-derived factor-1α (SDF-1α) were conducted at baseline and at 3 months after treatment with saxagliptin. A total of 31 patients with type 2 diabetes were included in the analysis. Saxagliptin significantly increased FMD from 3.1 ± 3.1% to 4.2 ± 2.4% (P = 0.032) and significantly decreased total cholesterol from 190 ± 24 mg/dL to 181 ± 25 mg/dL (P = 0.002), glucose from 160 ± 53 mg/dL to 133 ± 25 mg/dL (P < 0.001), HbA1c from 7.5 ± 0.6% to 7.0 ± 0.6% (P < 0.001), urine albumin-to-creatinine ratio from 63.8 ± 134.2 mg/g to 40.9 ± 83.0 mg/g (P = 0.043), and total SDF-1α from 2108 ± 243 pg/mL to 1284 ± 345 pg/mL (P < 0.001). These findings suggest that saxagliptin is effective for improving endothelial function