17 research outputs found

    Gas-sensing Properties of Photoluminescence-type Macroporous SnO2-based Sensors

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    ナノダイナミクス国際シンポジウム 平成22年1月21日(木) 於長崎大学Nagasaki Symposium on Nano-Dynamics 2010 (NSND2010), January 21, 2010, Nagasaki University, Nagasaki, Japan, Invited Lectur

    The Potential of ChatGPT as a Self-Diagnostic Tool in Common Orthopedic Diseases: Exploratory Study

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    BackgroundArtificial intelligence (AI) has gained tremendous popularity recently, especially the use of natural language processing (NLP). ChatGPT is a state-of-the-art chatbot capable of creating natural conversations using NLP. The use of AI in medicine can have a tremendous impact on health care delivery. Although some studies have evaluated ChatGPT’s accuracy in self-diagnosis, there is no research regarding its precision and the degree to which it recommends medical consultations. ObjectiveThe aim of this study was to evaluate ChatGPT’s ability to accurately and precisely self-diagnose common orthopedic diseases, as well as the degree of recommendation it provides for medical consultations. MethodsOver a 5-day course, each of the study authors submitted the same questions to ChatGPT. The conditions evaluated were carpal tunnel syndrome (CTS), cervical myelopathy (CM), lumbar spinal stenosis (LSS), knee osteoarthritis (KOA), and hip osteoarthritis (HOA). Answers were categorized as either correct, partially correct, incorrect, or a differential diagnosis. The percentage of correct answers and reproducibility were calculated. The reproducibility between days and raters were calculated using the Fleiss κ coefficient. Answers that recommended that the patient seek medical attention were recategorized according to the strength of the recommendation as defined by the study. ResultsThe ratios of correct answers were 25/25, 1/25, 24/25, 16/25, and 17/25 for CTS, CM, LSS, KOA, and HOA, respectively. The ratios of incorrect answers were 23/25 for CM and 0/25 for all other conditions. The reproducibility between days was 1.0, 0.15, 0.7, 0.6, and 0.6 for CTS, CM, LSS, KOA, and HOA, respectively. The reproducibility between raters was 1.0, 0.1, 0.64, –0.12, and 0.04 for CTS, CM, LSS, KOA, and HOA, respectively. Among the answers recommending medical attention, the phrases “essential,” “recommended,” “best,” and “important” were used. Specifically, “essential” occurred in 4 out of 125, “recommended” in 12 out of 125, “best” in 6 out of 125, and “important” in 94 out of 125 answers. Additionally, 7 out of the 125 answers did not include a recommendation to seek medical attention. ConclusionsThe accuracy and reproducibility of ChatGPT to self-diagnose five common orthopedic conditions were inconsistent. The accuracy could potentially be improved by adding symptoms that could easily identify a specific location. Only a few answers were accompanied by a strong recommendation to seek medical attention according to our study standards. Although ChatGPT could serve as a potential first step in accessing care, we found variability in accurate self-diagnosis. Given the risk of harm with self-diagnosis without medical follow-up, it would be prudent for an NLP to include clear language alerting patients to seek expert medical opinions. We hope to shed further light on the use of AI in a future clinical study

    Photoreactions of Endohedral Metallofullerene with Siliranes: Electronic Properties of Carbosilylated Lu3N@Ih-C80

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    Photochemical carbosilylation of Lu3N@Ih-C80 was performed using siliranes (silacyclopropanes) to afford the corresponding [5,6]- and [6,6]-adducts. Electrochemical studies indicated that the redox potentials of the carbosilylated derivatives were shifted cathodically in comparison with those of the [5,6]-pyrrolidino adducts. The electronic effect of the silirane addends on Lu3N@Ih-C80 was verified on the basis of density functional theory calculations

    Data Collection and Evaluation of AURORA-2 Japanese Corpus

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    ABSTRACT Speech recognition systems must still be improved when they are exposed to noisy environments. For this improvement, developments of the standard evaluation corpus and assessment technologies are essential. Recently the AURORA-2,3 corpus and their evaluation scenarios have had significant impacts on noisy speech recognition research. This paper introduces a Japanese noisy speech corpus and its evaluation scripts, called AURORA-2J. The AURORA-2J is a Japanese connected digits corpus. The data collection and evaluation scenarios are designed in the same way as AURORA-2 with the help of ETSI AURORA group. Furthermore, we have collected in-car speech corpus similar to AURORA-3. The in-car speech corpus includes Japanese connected digits and command words collected in a moving car. This paper describes the data collection, baseline scripts, and its baseline performance

    Crystal Structure, Thermal Behavior, and Photocatalytic Activity of NaBiO<sub>3</sub>·<i>n</i>H<sub>2</sub>O

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    The crystal structure of NaBiO<sub>3</sub>·<i>n</i>H<sub>2</sub>O was refined using synchrotron powder X-ray diffraction and was assigned to a trigonal unit cell (space group <i>P</i>3̅) consisting of layered structures formed by edge-sharing BiO<sub>6</sub> octahedra and consisting of an interlayer composed of water molecules sandwiched between two layers of sodium atoms, perpendicular to the <i>c</i> axis. An intermediate phase was observed during the dehydration of the hydrated compound. Density of state calculations showed hybridization of the Bi 6s and O 2p orbitals at the bottom of the conduction bands for both the hydrated and the dehydrated phases, which narrows the band gap and promotes their photocatalytic activity in the visible region
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