Developing an AI-assisted clinical decision support system to enhance in-patient holistic health care.

Holistic health care (HHC) is a synonym for complete patient care, and as such an efficient clinical decision support system (CDSS) for HHC is critical to support the judgement of physician's decision in response of patient's physical, emotional, social, economic, and spiritual needs. The field of artificial intelligence (AI) has evolved considerably in the past decades and many AI applications have been deployed in various contexts. Therefore, this study aims to propose an AI-assisted CDSS model that predicts patients in need of HHC and applies an improved recurrent neural network (RNN) model, long short-term memory (LSTM) for the prediction. The data sources include in-patient's comorbidity status and daily vital sign attributes such as blood pressure, heart rate, oxygen prescription, etc. A two-year dataset consisting of 121 thousand anonymized patient cases with 890 thousand physiological medical records was obtained from a medical center in Taiwan for system evaluation. Comparing with the rule-based expert system, the proposed AI-assisted CDSS improves sensitivity from 26.44% to 80.84% and specificity from 99.23% to 99.95%. The experimental results demonstrate that an AI-assisted CDSS could efficiently predict HHC patients.

Emission inventory and sources of polycyclic aromatic hydrocarbons in the atmosphere at a suburban area in Taiwan.

The application of a chemical mass balance air pollution model to ambient measurements of polycyclic aromatic hydrocarbons (PAHs) is presented. Sixteen air samples were collected at seven sites in a suburban area in Taiwan and analyzed for the concentration of 21 compounds between July 2001 and September 2001. Each ambient sample was evaluated for the PAH contribution from six sources (heavy oil combustion, natural gas combustion, coal combustion, diesel combustion, vehicles and municipal solid waste incinerator). Average predictions agree well with the emission inventory. By this method, the average contributions are 49%, 14%, 22%, 12%, and 2% from vehicles, heavy oil combustion, natural gas combustion, coal combustion and diesel combustion at these seven receptors. By far, vehicles are the major PAH emission sources and municipal solid waste incinerator is a minor contributor. The calculated result of particulate PAHs is compared with that of total (gaseous and particulate) PAHs. The estimate based on total PAHs is better than the estimate based on particulate PAHs only. Contributions of eight low reactive PAHs for the same emission sources and receptors were calculated. Atmospheric reactivity seems not a problem for source apportionment in this study.

Intraductal papillary carcinoma of bilateral breasts: a case report.

We report a 59-year-old woman presenting with a 2-month history of occasional bloody discharge from her right nipple and a palpable right breast mass on self-examination. The mammography revealed heterogeneously dense fibroglandular stromas of bilateral breasts, a lobulated mass in her right breast associated with faint pleomorphic microcalcifications, and, in addition, very faint focal granular microcalcifications in the left breast. Breast ultrasound revealed a lobulated and heterogeneous hypoechoic tumor with irregular margins at the right breast and a well-circumscribed tumor with heterogeneous echotexture at the left breast.