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Intelligence Testing

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101. Deep Learning-Based Noise Reduction Approach to Improve Speech Intelligibility for Cochlear Implant Recipients. (PubMed)

noise, at 0 and 5 dB SNR levels. Two conventional NR techniques and the proposed deep learning-based approach are used to process the noisy utterances. We qualitatively compare the NR approaches by the amplitude envelope and spectrogram plots of the processed utterances. Quantitative objective measures include (1) normalized covariance measure to test the intelligibility of the utterances processed by each of the NR approaches; and (2) speech recognition tests conducted by nine Mandarin-speaking CI (...) recipients. These nine CI recipients use their own clinical speech processors during testing.The experimental results of objective evaluation and listening test indicate that under challenging listening conditions, the proposed NC + DDAE NR approach yields higher intelligibility scores than the two compared classical NR techniques, under both matched and mismatched training-testing conditions.When compared to the two well-known conventional NR techniques under challenging listening condition

2018 Ear and hearing

102. Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images. (PubMed)

Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images. Image recognition using artificial intelligence with deep learning through convolutional neural networks (CNNs) has dramatically improved and been increasingly applied to medical fields for diagnostic imaging. We developed a CNN that can automatically detect gastric cancer in endoscopic images.A CNN-based diagnostic system was constructed based on Single Shot MultiBox (...) Detector architecture and trained using 13,584 endoscopic images of gastric cancer. To evaluate the diagnostic accuracy, an independent test set of 2296 stomach images collected from 69 consecutive patients with 77 gastric cancer lesions was applied to the constructed CNN.The CNN required 47 s to analyze 2296 test images. The CNN correctly diagnosed 71 of 77 gastric cancer lesions with an overall sensitivity of 92.2%, and 161 non-cancerous lesions were detected as gastric cancer, resulting

2018 Gastric Cancer

103. 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

104. 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

105. Development of Artificial Intelligence System for Detection and Diagnosis of Breast Lesion Using Mammography

Development of Artificial Intelligence System for Detection and Diagnosis of Breast Lesion Using Mammography Development of Artificial Intelligence System for Detection and Diagnosis of Breast Lesion Using Mammography - 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. Development of Artificial Intelligence System for Detection and Diagnosis of Breast Lesion Using Mammography 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

2018 Clinical Trials

106. 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

107. Effect of acupuncture at 3-points for intelligence on vascular dementia: Protocol for a systematic review and meta-analysis of randomized controlled trials. (PubMed)

Effect of acupuncture at 3-points for intelligence on vascular dementia: Protocol for a systematic review and meta-analysis of randomized controlled trials. Vascular dementia (VD) is a commonly-seen disease in the elderly. What is more, "Acupuncture at 3-points for intelligence" is one of the most important components of "Jin's three-needle therapy" created by Rui Jin, a professor of Guangzhou University of Chinese Medicine, which can be used in the VD patients. In this article, researchers (...) will assess the clinical efficacy and safety of acupuncture at 3-points for intelligence in the treatment of VD.A systematic literature search for articles up to September 2018 will be conducted using 9 databases: PubMed, Cochrane Library, Embase, CNKI, CBM, VIP, Wanfang database, OASIS, and CiNii. Inclusion criteria are randomized controlled trials (RCTs) of acupuncture at 3-points for intelligence on treating VD. The primary outcome measures will be scores reflecting the neurological function

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2018 Medicine

108. Impact of an intelligent chronic disease management system on patients with type 2 diabetes mellitus in a Beijing community. (PubMed)

Impact of an intelligent chronic disease management system on patients with type 2 diabetes mellitus in a Beijing community. Rapid demographic and economic changes have made chronic disease the number one health issue in China, contributing to more than 80% of the country's 10.3 million annual deaths and nearly 70% of its total disease burden (Wang et al., Toward a Healthy and Harmonious Life in China: Stemming the Rising Tide of Non-Communicable Diseases, 2011; Yip and Hsiao, Lancet 384: 805 (...) in Australia (Kelly et al., Aust J Prim Health 9:186-9, 2003). The ICDMS is an important tool in the implementation of patient-centered programs targeting chronic health issues, and its success is determined by factors, such as frequent contact between patients and doctors and effective website training for patients. This retrospective study used de-identified data from the Fangzhuang (Beijing) intelligent chronic disease management system (ICDMS) database to evaluate the effect of an intelligent chronic

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2018 BMC health services research

109. Targeted Estimation of the Relationship Between Childhood Adversity and Fluid Intelligence in a US Population Sample of Adolescents. (PubMed)

(n = 10,073), we examined the associations between 11 childhood adversities and intelligence, using targeted maximum likelihood estimation. Targeted maximum likelihood estimation incorporates machine learning to identify the relationships between exposures and outcomes without overfitting, including interactions and nonlinearity. The nonverbal score from the Kaufman Brief Intelligence Test was used as a standardized measure of fluid reasoning. Childhood adversities were grouped into deprivation (...) Targeted Estimation of the Relationship Between Childhood Adversity and Fluid Intelligence in a US Population Sample of Adolescents. Many studies have shown inverse associations between childhood adversity and intelligence, although most are based on small clinical samples and fail to account for the effects of multiple co-occurring adversities. Using data from the 2001-2004 National Comorbidity Survey Adolescent Supplement, a cross-sectional US population study of adolescents aged 13-18 years

2018 American Journal of Epidemiology

110. FDA permits Artificial intelligence-based in diabetes-related eye problems

FDA permits Artificial intelligence-based in diabetes-related eye problems FDA permits Artificial intelligence-based in diabetes-related eye problems - Sumer's Radiology Blog Top Ad unit 728 × 90 Radiology News radiology FDA permits Artificial intelligence-based in diabetes-related eye problems FDA permits Artificial intelligence-based in diabetes-related eye problems Reference and Further Reading FDA permits Artificial intelligence-based in diabetes-related eye problems Reviewed by Sumer (...) Sethi on Thursday, April 12, 2018 Rating: 5 Tags : Sumer Sethi About Dr. Sumer Sethi Number of Entries : 35 Unique blend of academic excellence and entrepreneurship, heading leading firms in India- Teleradiology Providers, pioneering company providing teleradiology services and DAMS (Delhi Academy of Medical Sciences) Premier test preparation institute in India for MD/MS/MCI preparation. He has also been an invited faculty member at various conferences, including Teleradiology in IRIA 2008 and 2011

2018 Sumer's Radiology Blog

111. Effects of Hearing Loss and Fast-Acting Compression on Amplitude Modulation Perception and Speech Intelligibility. (PubMed)

Effects of Hearing Loss and Fast-Acting Compression on Amplitude Modulation Perception and Speech Intelligibility. The purpose was to investigate the effects of hearing-loss and fast-acting compression on speech intelligibility and two measures of temporal modulation sensitivity.Twelve adults with normal hearing (NH) and 16 adults with mild to moderately severe sensorineural hearing loss were tested. Amplitude modulation detection and modulation-depth discrimination (MDD) thresholds (...) with sinusoidal carriers of 1 or 5 kHz and modulators in the range from 8 to 256 Hz were used as measures of temporal modulation sensitivity. Speech intelligibility was assessed by obtaining speech reception thresholds in stationary and fluctuating background noise. All thresholds were obtained with and without compression (using a fixed compression ratio of 2:1).For modulation detection, the thresholds were similar or lower for the group with hearing loss than for the group with NH. In contrast, the MDD

2018 Ear and hearing

112. A "Goldilocks" Approach to Hearing Aid Self-Fitting: Ear-Canal Output and Speech Intelligibility Index. (PubMed)

A "Goldilocks" Approach to Hearing Aid Self-Fitting: Ear-Canal Output and Speech Intelligibility Index. The objective was to determine self-adjusted output response and speech intelligibility index (SII) in individuals with mild to moderate hearing loss and to measure the effects of prior hearing aid experience.Thirteen hearing aid users and 13 nonusers, with similar group-mean pure-tone thresholds, listened to prerecorded and preprocessed sentences spoken by a man. Starting with a generic (...) level and spectrum, participants adjusted (1) overall level, (2) high-frequency boost, and (3) low-frequency cut. Participants took a speech perception test after an initial adjustment before making a final adjustment. The three self-selected parameters, along with individual thresholds and real-ear-to-coupler differences, were used to compute output levels and SIIs for the starting and two self-adjusted conditions. The values were compared with an NAL second nonlinear threshold-based prescription

2018 Ear and hearing

113. Building predictive in vitro pulmonary toxicity assays using high-throughput imaging and artificial intelligence (PubMed)

Building predictive in vitro pulmonary toxicity assays using high-throughput imaging and artificial intelligence Human lungs are susceptible to the toxicity induced by soluble xenobiotics. However, the direct cellular effects of many pulmonotoxic chemicals are not always clear, and thus, a general in vitro assay for testing pulmonotoxicity applicable to a wide variety of chemicals is not currently available. Here, we report a study that uses high-throughput imaging and artificial intelligence (...) information (88.8% balance accuracy, 84.6% sensitivity, and 93.0% specificity). In comparison, the predictivity of a standard cell-viability assay on the same set of chemicals is much lower (77.1% balanced accuracy, 84.6% sensitivity, and 69.5% specificity). We also used the assay to evaluate 17 additional test chemicals with unknown/unclear human pulmonotoxicity, and experimentally confirmed that many of the pulmonotoxic reference and predicted-positive test chemicals induce DNA strand breaks

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2018 Archives of toxicology

114. Intelligent Fault Diagnosis of Delta 3D Printers Using Attitude Sensors Based on Support Vector Machines (PubMed)

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.

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2018 Sensors (Basel, Switzerland)

115. Use of a Deep Recurrent Neural Network to Reduce Wind Noise: Effects on Judged Speech Intelligibility and Sound Quality (PubMed)

participants were tested, nine with normal hearing and nine with mild-to-moderate hearing impairment. Frequency-dependent linear amplification was provided for the latter. Processing using the RNN was significantly preferred over no processing by both subject groups for both subjective intelligibility and sound quality, although the magnitude of the preferences was small. High-pass filtering (HPF) was not significantly preferred over no processing. Although RNN was significantly preferred over HPF only (...) Use of a Deep Recurrent Neural Network to Reduce Wind Noise: Effects on Judged Speech Intelligibility and Sound Quality Despite great advances in hearing-aid technology, users still experience problems with noise in windy environments. The potential benefits of using a deep recurrent neural network (RNN) for reducing wind noise were assessed. The RNN was trained using recordings of the output of the two microphones of a behind-the-ear hearing aid in response to male and female speech at various

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2018 Trends in hearing

116. 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

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

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

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2018 Advances in Cognitive Psychology

118. Evaluating the relationship between emotional intelligence and cognitive disorders in patients with Multiple Sclerosis (PubMed)

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

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2018 Iranian journal of neurology

119. Artificial Intelligence Estimation of Carotid-Femoral Pulse Wave Velocity using Carotid Waveform (PubMed)

Artificial Intelligence Estimation of Carotid-Femoral Pulse Wave Velocity using Carotid Waveform In this article, we offer an artificial intelligence method to estimate the carotid-femoral Pulse Wave Velocity (PWV) non-invasively from one uncalibrated carotid waveform measured by tonometry and few routine clinical variables. Since the signal processing inputs to this machine learning algorithm are sensor agnostic, the presented method can accompany any medical instrument that provides (...) a calibrated or uncalibrated carotid pressure waveform. Our results show that, for an unseen hold back test set population in the age range of 20 to 69, our model can estimate PWV with a Root-Mean-Square Error (RMSE) of 1.12 m/sec compared to the reference method. The results convey the fact that this model is a reliable surrogate of PWV. Our study also showed that estimated PWV was significantly associated with an increased risk of CVDs.

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2018 Scientific reports

120. Comparison of SVM, RF and ELM on an Electronic Nose for the Intelligent Evaluation of Paraffin Samples (PubMed)

Comparison of SVM, RF and ELM on an Electronic Nose for the Intelligent Evaluation of Paraffin Samples Paraffin odor intensity is an important quality indicator when a paraffin inspection is performed. Currently, paraffin odor level assessment is mainly dependent on an artificial sensory evaluation. In this paper, we developed a paraffin odor analysis system to classify and grade four kinds of paraffin samples. The original feature set was optimized using Principal Component Analysis (PCA (...) to the test set was above 0.87. Through comprehensive comparison, the generalization of the model based on ELM was superior to those based on SVM and RF. The scoring errors for the three models were 0.0016-0.3494, lower than the error of 0.5-1.0 measured by industry standard experts, meaning these methods have a higher prediction accuracy for scoring paraffin level.

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2018 Sensors (Basel, Switzerland)

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