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Intelligence Testing

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161. Automatic detection of mycobacterium tuberculosis using artificial intelligence (Full text)

Automatic detection of mycobacterium tuberculosis using artificial intelligence Tuberculosis (TB) is a global issue that seriously endangers public health. Pathology is one of the most important means for diagnosing TB in clinical practice. To confirm TB as the diagnosis, finding specially stained TB bacilli under a microscope is critical. Because of the very small size and number of bacilli, it is a time-consuming and strenuous work even for experienced pathologists, and this strenuosity often (...) leads to low detection rate and false diagnoses. We investigated the clinical efficacy of an artificial intelligence (AI)-assisted detection method for acid-fast stained TB bacillus.We built a convolutional neural networks (CNN) model, named tuberculosis AI (TB-AI), specifically to recognize TB bacillus. The training set contains 45 samples, including 30 positive cases and 15 negative cases, where bacilli are labeled by human pathologists. Upon training the neural network model, 201 samples (108

2018 Journal of thoracic disease PubMed abstract

162. Clinician-Driven Design of VitalPAD–An Intelligent Monitoring and Communication Device to Improve Patient Safety in the Intensive Care Unit (Full text)

Clinician-Driven Design of VitalPAD–An Intelligent Monitoring and Communication Device to Improve Patient Safety in the Intensive Care Unit The pediatric intensive care unit (ICU) is a complex environment, in which a multidisciplinary team of clinicians (registered nurses, respiratory therapists, and physicians) continually observe and evaluate patient information. Data are provided by multiple, and often physically separated sources, cognitive workload is high, and team communication can (...) be challenging. Our aim is to combine information from multiple monitoring and therapeutic devices in a mobile application, the VitalPAD, to improve the efficiency of clinical decision-making, communication, and thereby patient safety. We observed individual ICU clinicians, multidisciplinary rounds, and handover procedures for 54 h to identify data needs, workflow, and existing cognitive aid use and limitations. A prototype was developed using an iterative participatory design approach; usability testing

2018 IEEE journal of translational engineering in health and medicine PubMed abstract

163. Aerial Mapping of Forests Affected by Pathogens Using UAVs, Hyperspectral Sensors, and Artificial Intelligence (Full text)

Aerial Mapping of Forests Affected by Pathogens Using UAVs, Hyperspectral Sensors, and Artificial Intelligence The environmental and economic impacts of exotic fungal species on natural and plantation forests have been historically catastrophic. Recorded surveillance and control actions are challenging because they are costly, time-consuming, and hazardous in remote areas. Prolonged periods of testing and observation of site-based tests have limitations in verifying the rapid proliferation (...) of exotic pathogens and deterioration rates in hosts. Recent remote sensing approaches have offered fast, broad-scale, and affordable surveys as well as additional indicators that can complement on-ground tests. This paper proposes a framework that consolidates site-based insights and remote sensing capabilities to detect and segment deteriorations by fungal pathogens in natural and plantation forests. This approach is illustrated with an experimentation case of myrtle rust (Austropuccinia psidii

2018 Sensors (Basel, Switzerland) PubMed abstract

164. Artificial Intelligence Approach for Variant Reporting (Full text)

Artificial Intelligence Approach for Variant Reporting Next-generation sequencing technologies are actively applied in clinical oncology. Bioinformatics pipeline analysis is an integral part of this process; however, humans cannot yet realize the full potential of the highly complex pipeline output. As a result, the decision to include a variant in the final report during routine clinical sign-out remains challenging.We used an artificial intelligence approach to capture the collective clinical (...) sign-out experience of six board-certified molecular pathologists to build and validate a decision support tool for variant reporting. We extracted all reviewed and reported variants from our clinical database and tested several machine learning models. We used 10-fold cross-validation for our variant call prediction model, which derives a contiguous prediction score from 0 to 1 (no to yes) for clinical reporting.For each of the 19,594 initial training variants, our pipeline generates approximately

2018 JCO clinical cancer informatics PubMed abstract

165. An Analysis of Individual Differences in Recognizing Monosyllabic Words Under the Speech Intelligibility Index Framework (Full text)

An Analysis of Individual Differences in Recognizing Monosyllabic Words Under the Speech Intelligibility Index Framework Individual differences in the recognition of monosyllabic words, either in isolation (NU6 test) or in sentence context (SPIN test), were investigated under the theoretical framework of the speech intelligibility index (SII). An adaptive psychophysical procedure, namely the quick-band-importance-function procedure, was developed to enable the fitting of the SII model (...) to individual listeners. Using this procedure, the band importance function (i.e., the relative weights of speech information across the spectrum) and the link function relating the SII to recognition scores can be simultaneously estimated while requiring only 200 to 300 trials of testing. Octave-frequency band importance functions and link functions were estimated separately for NU6 and SPIN materials from 30 normal-hearing listeners who were naïve to speech recognition experiments. For each type of speech

2018 Trends in hearing PubMed abstract

166. IDEAL: Artificial Intelligence and Big Data for Early Lung Cancer Diagnosis Study

IDEAL: Artificial Intelligence and Big Data for Early Lung Cancer Diagnosis Study IDEAL: Artificial Intelligence and Big Data for Early Lung Cancer Diagnosis Study - Full Text View - ClinicalTrials.gov Hide glossary Glossary Study record managers: refer to the if submitting registration or results information. Search for terms x × Study Record Detail Saved Studies Save this study Warning You have reached the maximum number of saved studies (100). Please remove one or more studies before adding (...) more. IDEAL: Artificial Intelligence and Big Data for Early Lung Cancer Diagnosis Study (IDEAL) The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. of clinical studies and talk to your health care provider before participating. Read our for details. ClinicalTrials.gov Identifier: NCT03753724 Recruitment Status : Recruiting First Posted : November 27, 2018

2018 Clinical Trials

167. Elucidating the Functional Relationship Between Speed of Information Processing and Speed-, Capacity-, and Memory-Related Aspects of Psychometric Intelligence (Full text)

task and the Berlin Intelligence Structure (BIS) test were administered to 240 participants. From the BIS test, indicators of BIS -Capacity, BIS -Speed, and BIS -Memory were determined. By means of fixed-links modeling, we subdivided variance in reaction time from the Hick task into a component representing individual differences in speed directly related to the systematically increased number of possible responses and another component representing individual differences in speed associated (...) Elucidating the Functional Relationship Between Speed of Information Processing and Speed-, Capacity-, and Memory-Related Aspects of Psychometric Intelligence Numerous studies reported a positive relationship between speed of information processing (SIP) and the g factor of intelligence. Only very few studies, however, examined SI P's relationship to speed-, capacity-, and memory-related aspects of psychometric intelligence. In order to further elucidate this relationship, a Hick reaction time

2018 Advances in Cognitive Psychology PubMed abstract

168. Associations between emotional intelligence, empathy and personality in Japanese medical students (Full text)

Associations between emotional intelligence, empathy and personality in Japanese medical students It is known that empathic communication is important for physicians to achieve higher patient satisfaction and health outcomes. Emotional intelligence (EI), empathy and personality in medical students predict students' individual disposition and their emotional and empathic perceptions. This study aimed to investigate: 1) The association between empathy, EI and personality, and 2) Gender (...) differences in the association between empathy, EI and personality.Participants were 357 1st year medical students from 2008 to 2011 at one medical school in Japan. Students completed self-report questionnaires comprising three validated instruments measuring EI: Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF), empathy: Jefferson Scale of Physician Empathy- student version (JSPE) and personality: NEO-Five-Factor Inventory (NEO-FFI), which explores 5 dimensions of personality Neuroticism

2018 BMC medical education PubMed abstract

169. Intelligent Fault Diagnosis of Delta 3D Printers Using Attitude Sensors Based on Support Vector Machines (Full text)

Intelligent Fault Diagnosis of Delta 3D Printers Using Attitude Sensors Based on Support Vector Machines Health condition is a vital factor affecting printing quality for a 3D printer. In this work, an attitude monitoring approach is proposed to diagnose the fault of the delta 3D printer using support vector machines (SVM). An attitude sensor was mounted on the moving platform of the printer to monitor its 3-axial attitude angle, angular velocity, vibratory acceleration and magnetic field (...) training and testing. On the other hand, a back propagation neural network (BPNN) was also applied to diagnose fault using the same data. The best fault diagnosis accuracy (94.44%) was obtained when all channels of the attitude monitoring data were used with SVM modelling. The results indicate that the attitude monitoring with SVM is an effective method for the fault diagnosis of delta 3D printers.

2018 Sensors (Basel, Switzerland) PubMed abstract

170. Evaluation of the Effectiveness of a Program of Emotional Intelligence in Adolescents With Type 1 Diabetes (INTEDI)

Evaluation of the Effectiveness of a Program of Emotional Intelligence in Adolescents With Type 1 Diabetes (INTEDI) Evaluation of the Effectiveness of a Program of Emotional Intelligence in Adolescents With Type 1 Diabetes (INTEDI) - Full Text View - ClinicalTrials.gov Hide glossary Glossary Study record managers: refer to the if submitting registration or results information. Search for terms x × Study Record Detail Saved Studies Save this study Warning You have reached the maximum number (...) of saved studies (100). Please remove one or more studies before adding more. Evaluation of the Effectiveness of a Program of Emotional Intelligence in Adolescents With Type 1 Diabetes (INTEDI) (INTEDI) The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. of clinical studies and talk to your health care provider before participating. Read our for details

2018 Clinical Trials

171. A Multi-center Study on the Artificial Intelligence Enabled Diabetic Retinopathy Screening Based on Fundus Images

A Multi-center Study on the Artificial Intelligence Enabled Diabetic Retinopathy Screening Based on Fundus Images A Multi-center Study on the Artificial Intelligence Enabled Diabetic Retinopathy Screening Based on Fundus Images - Full Text View - ClinicalTrials.gov Hide glossary Glossary Study record managers: refer to the if submitting registration or results information. Search for terms x × Study Record Detail Saved Studies Save this study Warning You have reached the maximum number of saved (...) studies (100). Please remove one or more studies before adding more. A Multi-center Study on the Artificial Intelligence Enabled Diabetic Retinopathy Screening Based on Fundus Images The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. of clinical studies and talk to your health care provider before participating. Read our for details. ClinicalTrials.gov

2018 Clinical Trials

172. Artificial Intelligence to Assess the Association Between Facial Characteristics and Coronary Artery Diseases

Perspective: Cross-Sectional Official Title: Artificial Intelligence to Assess the Association Between Facial Characteristics and Coronary Artery Diseases Actual Study Start Date : July 10, 2017 Estimated Primary Completion Date : December 31, 2019 Estimated Study Completion Date : February 28, 2020 Resource links provided by the National Library of Medicine related topics: Groups and Cohorts Go to Group/Cohort Intervention/treatment Model establishment and test group Patients undergoing coronary (...) Artificial Intelligence to Assess the Association Between Facial Characteristics and Coronary Artery Diseases Artificial Intelligence to Assess the Association Between Facial Characteristics and Coronary Artery Diseases - Full Text View - ClinicalTrials.gov Hide glossary Glossary Study record managers: refer to the if submitting registration or results information. Search for terms x × Study Record Detail Saved Studies Save this study Warning You have reached the maximum number of saved studies

2018 Clinical Trials

173. Tailored Drug Titration Through Artificial Intelligence

by (Responsible Party): Optima Integrated Health Study Details Study Description Go to Brief Summary: ARTERY is a randomized clinical trial that investigates the benefit of a predictive modeling artificial intelligence in improving the management of anti-hypertensive medication treatment. Condition or disease Intervention/treatment Phase Hypertension Other: optima4BP Not Applicable Detailed Description: The goal of the proposed research is to test a connected medication management platform technology (...) Tailored Drug Titration Through Artificial Intelligence Tailored Drug Titration Through Artificial Intelligence - Full Text View - ClinicalTrials.gov Hide glossary Glossary Study record managers: refer to the if submitting registration or results information. Search for terms x × Study Record Detail Saved Studies Save this study Warning You have reached the maximum number of saved studies (100). Please remove one or more studies before adding more. Tailored Drug Titration Through Artificial

2018 Clinical Trials

174. SYNERGY-AI: Artificial Intelligence Based Precision Oncology Clinical Trial Matching and Registry

SYNERGY-AI: Artificial Intelligence Based Precision Oncology Clinical Trial Matching and Registry SYNERGY-AI: Artificial Intelligence Based Precision Oncology Clinical Trial Matching and Registry - Full Text View - ClinicalTrials.gov Hide glossary Glossary Study record managers: refer to the if submitting registration or results information. Search for terms x × Study Record Detail Saved Studies Save this study Warning You have reached the maximum number of saved studies (100). Please remove (...) one or more studies before adding more. SYNERGY-AI: Artificial Intelligence Based Precision Oncology Clinical Trial Matching and Registry The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. of clinical studies and talk to your health care provider before participating. Read our for details. ClinicalTrials.gov Identifier: NCT03452774 Recruitment Status

2018 Clinical Trials

175. Validation of the Utility of Ophthalmology Intelligent Diagnostic System

Go to Arm Intervention/treatment Experimental: Eligible patients for AI test. Device: ophthalmology diagnostic system. An artificial intelligence to make comprehensive evaluation and treatment decision of ocular diseases. Device: Ophthalmology diagnostic system. An artificial intelligence to make comprehensive evaluation and treatment decision of ocular diseases. Outcome Measures Go to Primary Outcome Measures : The proportion of accurate, mistaken and miss detection of the ophthalmology (...) Validation of the Utility of Ophthalmology Intelligent Diagnostic System Validation of the Utility of Ophthalmology Intelligent Diagnostic System - Full Text View - ClinicalTrials.gov Hide glossary Glossary Study record managers: refer to the if submitting registration or results information. Search for terms x × Study Record Detail Saved Studies Save this study Warning You have reached the maximum number of saved studies (100). Please remove one or more studies before adding more. Validation

2018 Clinical Trials

176. Artificial Intelligence Screening on Patients With Primary Angle Closure Glaucoma

Artificial Intelligence Screening on Patients With Primary Angle Closure Glaucoma Artificial Intelligence Screening on Patients With Primary Angle Closure Glaucoma - Full Text View - ClinicalTrials.gov Hide glossary Glossary Study record managers: refer to the if submitting registration or results information. Search for terms x × Study Record Detail Saved Studies Save this study Warning You have reached the maximum number of saved studies (100). Please remove one or more studies before adding (...) more. Artificial Intelligence Screening on Patients With Primary Angle Closure Glaucoma (AI) The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. of clinical studies and talk to your health care provider before participating. Read our for details. ClinicalTrials.gov Identifier: NCT03611387 Recruitment Status : Recruiting First Posted : August 2, 2018 Last

2018 Clinical Trials

177. Validation of an Artificial Intelligence-based Algorithm for Skeletal Age Assessment

Validation of an Artificial Intelligence-based Algorithm for Skeletal Age Assessment Validation of an Artificial Intelligence-based Algorithm for Skeletal Age Assessment - Full Text View - ClinicalTrials.gov Hide glossary Glossary Study record managers: refer to the if submitting registration or results information. Search for terms x × Study Record Detail Saved Studies Save this study Warning You have reached the maximum number of saved studies (100). Please remove one or more studies before (...) adding more. Validation of an Artificial Intelligence-based Algorithm for Skeletal Age Assessment The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our for details. ClinicalTrials.gov Identifier: NCT03530098 Recruitment Status : Enrolling by invitation First Posted : May 21, 2018 Last Update Posted : February 20, 2019 Sponsor: Stanford University

2018 Clinical Trials

178. Emotional Intelligence in Patients With Addictive Disorder

and Repair. Each of these three subscales consists of eight items with a 5-point Likert response format (ranging from 1 to 5). Subscale total scores are obtained by summing responses to all items and thus range from 8 to 40, with higher scores indicating greater level of the characteristic assessed. Score on an ability measure of emotional intelligence, the Spanish version of the Mayer-Salovey-Caruso Emotional Intelligence Test (Extremera & Fernández-Berrocal, 2016). [ Time Frame: Pre-intervention only (...) ] The Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) consists of 141 items that yield an overall emotional intelligence (EI) score and two EI area scores: the Experiential EI and Strategic EI scores. The aforementioned scores have a mean of 100 and a standard deviation of 15, with higher scores indicating greater emotional intelligence. Secondary Outcome Measures : Change in self-esteem, measured with the Spanish version of the Rosenberg Self-Esteem Scale (Martin-Albo, Núñez, Navarro & Grijalvo

2018 Clinical Trials

179. Evaluating the relationship between emotional intelligence and cognitive disorders in patients with Multiple Sclerosis (Full text)

between emotional intelligence and cognitive disorders in patients with Multiple Sclerosis (MS). Methods: The demographic data of 92 MS patients participating in this study were recorded. The emotional intelligence and cognitive disorders were studied using the Bradberry-Greaves, and MS Neuropsychological Questionnaire (MSNQ) tests, respectively. Results: 16 men and 76 women were considered in this study. The mean age of the participants was 33.4 years, the mean duration of the disease was 6.8 years (...) Evaluating the relationship between emotional intelligence and cognitive disorders in patients with Multiple Sclerosis Background: Emotional intelligence refers to a process through which an individual is not only capable of understanding his/her/others' emotions, but also is able to manage them. Emotional intelligence can get disturbed due to different neurological diseases. Since cognition and emotion are directly and closely related, the present study aims to evaluate the relationship

2018 Iranian journal of neurology PubMed abstract

180. The Effect of Self-Care Education on Emotional Intelligence and HbA1c level in Patients with Type 2 Diabetes Mellitus: A Randomized Controlled Clinical Trial (Full text)

The Effect of Self-Care Education on Emotional Intelligence and HbA1c level in Patients with Type 2 Diabetes Mellitus: A Randomized Controlled Clinical Trial The role of Emotional Intelligence (EI) in glycemic control in type 2 Diabetes Mellitus (DM) has not been fully understood. The present study aimed to investigate the effect of self-care education on EI and hemoglobin glycosylated (HbA1c) in patients with type 2 diabetes.In this randomized controlled clinical trial, 48 patients with type 2 (...) DM referred to Shahid Motahari Diabetes Center in 2015 were divided into an intervention and a control group using block randomization. The study data were collected using Bar-On questionnaire and blood testing immediately and two months after the intervention. The educational content was presented to the intervention group through 1-1:30-hour sessions held once a week for 8 continuous weeks. The control group, however, only received the clinic's routine cares.The results showed a significant

2018 International journal of community based nursing and midwifery Controlled trial quality: uncertain PubMed abstract

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