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  1. Book ; Online: Prediction of gaze direction using Convolutional Neural Networks for Autism diagnosis

    Núñez-Fernández, Dennis / Porras-Barrientos, Franklin / Vittet-Mondoñedo, Macarena / Gilman, Robert H. / Zimic, Mirko

    2019  

    Abstract: Autism is a developmental disorder that affects social interaction and communication of children. The gold standard diagnostic tools are very difficult to use and time consuming. However, diagnostic could be deduced from child gaze preferences by looking ...

    Abstract Autism is a developmental disorder that affects social interaction and communication of children. The gold standard diagnostic tools are very difficult to use and time consuming. However, diagnostic could be deduced from child gaze preferences by looking a video with social and abstract scenes. In this work, we propose an algorithm based on convolutional neural networks to predict gaze direction for a fast and effective autism diagnosis. Early results show that our algorithm achieves real-time response and robust high accuracy for prediction of gaze direction.

    Comment: LatinX in AI Research at NeurIPS 2019
    Keywords Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Human-Computer Interaction ; Electrical Engineering and Systems Science - Image and Video Processing
    Publishing date 2019-10-25
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Developing an eye-tracking algorithm as a potential tool for early diagnosis of autism spectrum disorder in children.

    Vargas-Cuentas, Natalia I / Roman-Gonzalez, Avid / Gilman, Robert H / Barrientos, Franklin / Ting, James / Hidalgo, Daniela / Jensen, Kelly / Zimic, Mirko

    PloS one

    2017  Volume 12, Issue 11, Page(s) e0188826

    Abstract: Background: Autism spectrum disorder (ASD) currently affects nearly 1 in 160 children worldwide. In over two-thirds of evaluations, no validated diagnostics are used and gold standard diagnostic tools are used in less than 5% of evaluations. Currently, ... ...

    Abstract Background: Autism spectrum disorder (ASD) currently affects nearly 1 in 160 children worldwide. In over two-thirds of evaluations, no validated diagnostics are used and gold standard diagnostic tools are used in less than 5% of evaluations. Currently, the diagnosis of ASD requires lengthy and expensive tests, in addition to clinical confirmation. Therefore, fast, cheap, portable, and easy-to-administer screening instruments for ASD are required. Several studies have shown that children with ASD have a lower preference for social scenes compared with children without ASD. Based on this, eye-tracking and measurement of gaze preference for social scenes has been used as a screening tool for ASD. Currently available eye-tracking software requires intensive calibration, training, or holding of the head to prevent interference with gaze recognition limiting its use in children with ASD.
    Methods: In this study, we designed a simple eye-tracking algorithm that does not require calibration or head holding, as a platform for future validation of a cost-effective ASD potential screening instrument. This system operates on a portable and inexpensive tablet to measure gaze preference of children for social compared to abstract scenes. A child watches a one-minute stimulus video composed of a social scene projected on the left side and an abstract scene projected on the right side of the tablet's screen. We designed five stimulus videos by changing the social/abstract scenes. Every child observed all the five videos in random order. We developed an eye-tracking algorithm that calculates the child's gaze preference for the social and abstract scenes, estimated as the percentage of the accumulated time that the child observes the left or right side of the screen, respectively. Twenty-three children without a prior history of ASD and 8 children with a clinical diagnosis of ASD were evaluated. The recorded video of the child´s eye movement was analyzed both manually by an observer and automatically by our algorithm.
    Results: This study demonstrates that the algorithm correctly differentiates visual preference for either the left or right side of the screen (social or abstract scenes), identifies distractions, and maintains high accuracy compared to the manual classification. The error of the algorithm was 1.52%, when compared to the gold standard of manual observation.
    Discussion: This tablet-based gaze preference/eye-tracking algorithm can estimate gaze preference in both children with ASD and without ASD to a high degree of accuracy, without the need for calibration, training, or restraint of the children. This system can be utilized in low-resource settings as a portable and cost-effective potential screening tool for ASD.
    MeSH term(s) Algorithms ; Autism Spectrum Disorder/diagnosis ; Child ; Child, Preschool ; Computer Graphics ; Early Diagnosis ; Eye Movements ; Female ; Humans ; Male ; User-Computer Interface
    Language English
    Publishing date 2017-11-30
    Publishing country United States
    Document type Journal Article ; Validation Study
    ISSN 1932-6203
    ISSN (online) 1932-6203
    DOI 10.1371/journal.pone.0188826
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  3. Book ; Online: Portable system for the prediction of anemia based on the ocular conjunctiva using Artificial Intelligence

    Saldivar-Espinoza, Bryan / Núñez-Fernández, Dennis / Porras-Barrientos, Franklin / Alva-Mantari, Alicia / Leslie, Lisa Suzanne / Zimic, Mirko

    2019  

    Abstract: Anemia is a major health burden worldwide. Examining the hemoglobin level of blood is an important way to achieve the diagnosis of anemia, but it requires blood drawing and a blood test. In this work we propose a non-invasive, fast, and cost-effective ... ...

    Abstract Anemia is a major health burden worldwide. Examining the hemoglobin level of blood is an important way to achieve the diagnosis of anemia, but it requires blood drawing and a blood test. In this work we propose a non-invasive, fast, and cost-effective screening test for iron-deficiency anemia in Peruvian young children. Our initial results show promising evidence for detecting conjunctival pallor anemia and Artificial Intelligence techniques with photos taken with a popular smartphone.

    Comment: LatinX in AI Research at NeurIPS 2019
    Keywords Electrical Engineering and Systems Science - Image and Video Processing ; Computer Science - Computer Vision and Pattern Recognition
    Publishing date 2019-10-25
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Autism Detection in Children by Combined Use of Gaze Preference and the M-CHAT-R in a Resource-Scarce Setting.

    Jensen, Kelly / Noazin, Sassan / Bitterfeld, Leandra / Carcelen, Andrea / Vargas-Cuentas, Natalia I / Hidalgo, Daniela / Valenzuela, Alejandra / Roman-Gonzalez, Avid / Krebs, Casey / Clement, Vincent / Nolan, Cody / Barrientos, Franklin / Mendoza, Ardi Knobel / Noriega-Donis, Paola / Palacios, Claudia / Ramirez, Andrea / Vittet, Macarena / Hafeez, Emil / Torres-Viso, Mariana /
    Velarde, Myriam / Moulton, Lawrence H / Powers, Michael D / Gilman, Robert H / Zimic, Mirko

    Journal of autism and developmental disorders

    2021  Volume 51, Issue 3, Page(s) 994–1006

    Abstract: Most children with autism spectrum disorder (ASD), in resource-limited settings (RLS), are diagnosed after the age of four. Our work confirmed and extended results of Pierce that eye tracking could discriminate between typically developing (TD) children ... ...

    Abstract Most children with autism spectrum disorder (ASD), in resource-limited settings (RLS), are diagnosed after the age of four. Our work confirmed and extended results of Pierce that eye tracking could discriminate between typically developing (TD) children and those with ASD. We demonstrated the initial 15 s was at least as discriminating as the entire video. We evaluated the GP-MCHAT-R, which combines the first 15 s of manually-coded gaze preference (GP) video with M-CHAT-R results on 73 TD children and 28 children with ASD, 36-99 months of age. The GP-MCHAT-R (AUC = 0.89 (95%CI: 0.82-0.95)), performed significantly better than the MCHAT-R (AUC = 0.78 (95%CI: 0.71-0.85)) and gaze preference (AUC = 0.76 (95%CI: 0.64-0.88)) alone. This tool may enable early screening for ASD in RLS.
    MeSH term(s) Autism Spectrum Disorder/diagnosis ; Autism Spectrum Disorder/epidemiology ; Autism Spectrum Disorder/physiopathology ; Checklist/methods ; Checklist/standards ; Child ; Child, Preschool ; Eye-Tracking Technology/standards ; Female ; Fixation, Ocular/physiology ; Health Resources/standards ; Humans ; Male ; Mass Screening/methods ; Mass Screening/standards ; Peru/epidemiology
    Language English
    Publishing date 2021-02-16
    Publishing country United States
    Document type Journal Article
    ZDB-ID 391999-7
    ISSN 1573-3432 ; 0162-3257
    ISSN (online) 1573-3432
    ISSN 0162-3257
    DOI 10.1007/s10803-021-04878-0
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

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  5. Article ; Online: Automatic classification of pediatric pneumonia based on lung ultrasound pattern recognition.

    Correa, Malena / Zimic, Mirko / Barrientos, Franklin / Barrientos, Ronald / Román-Gonzalez, Avid / Pajuelo, Mónica J / Anticona, Cynthia / Mayta, Holger / Alva, Alicia / Solis-Vasquez, Leonardo / Figueroa, Dante Anibal / Chavez, Miguel A / Lavarello, Roberto / Castañeda, Benjamín / Paz-Soldán, Valerie A / Checkley, William / Gilman, Robert H / Oberhelman, Richard

    PloS one

    2018  Volume 13, Issue 12, Page(s) e0206410

    Abstract: Pneumonia is one of the major causes of child mortality, yet with a timely diagnosis, it is usually curable with antibiotic therapy. In many developing regions, diagnosing pneumonia remains a challenge, due to shortages of medical resources. Lung ... ...

    Abstract Pneumonia is one of the major causes of child mortality, yet with a timely diagnosis, it is usually curable with antibiotic therapy. In many developing regions, diagnosing pneumonia remains a challenge, due to shortages of medical resources. Lung ultrasound has proved to be a useful tool to detect lung consolidation as evidence of pneumonia. However, diagnosis of pneumonia by ultrasound has limitations: it is operator-dependent, and it needs to be carried out and interpreted by trained personnel. Pattern recognition and image analysis is a potential tool to enable automatic diagnosis of pneumonia consolidation without requiring an expert analyst. This paper presents a method for automatic classification of pneumonia using ultrasound imaging of the lungs and pattern recognition. The approach presented here is based on the analysis of brightness distribution patterns present in rectangular segments (here called "characteristic vectors") from the ultrasound digital images. In a first step we identified and eliminated the skin and subcutaneous tissue (fat and muscle) in lung ultrasound frames, and the "characteristic vectors"were analyzed using standard neural networks using artificial intelligence methods. We analyzed 60 lung ultrasound frames corresponding to 21 children under age 5 years (15 children with confirmed pneumonia by clinical examination and X-rays, and 6 children with no pulmonary disease) from a hospital based population in Lima, Peru. Lung ultrasound images were obtained using an Ultrasonix ultrasound device. A total of 1450 positive (pneumonia) and 1605 negative (normal lung) vectors were analyzed with standard neural networks, and used to create an algorithm to differentiate lung infiltrates from healthy lung. A neural network was trained using the algorithm and it was able to correctly identify pneumonia infiltrates, with 90.9% sensitivity and 100% specificity. This approach may be used to develop operator-independent computer algorithms for pneumonia diagnosis using ultrasound in young children.
    MeSH term(s) Child ; Child, Preschool ; Humans ; Image Processing, Computer-Assisted/methods ; Infant ; Lung/diagnostic imaging ; Male ; Neural Networks, Computer ; Pneumonia/classification ; Pneumonia/diagnostic imaging ; Ultrasonography
    Language English
    Publishing date 2018-12-05
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ISSN 1932-6203
    ISSN (online) 1932-6203
    DOI 10.1371/journal.pone.0206410
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  6. Article ; Online: Risk factors of breast cancer in Mexican women

    Calderón-Garcidueñas Ana Laura / Parás-Barrientos Franklin Uriel / Cárdenas-Ibarra Lilia / González-Guerrero Juan Francisco / Villarreal-Ríos Enrique / Staines-Boone Tamara / Barrera-Saldaña Hugo A.

    Salud Pública de México, Vol 42, Iss 1, Pp 26-

    2000  Volume 33

    Abstract: OBJECTIVE: To investigate the association between family history (FH) of neoplasia, gyneco-obstetric factors and breast cancer (BC) in a case--control study. In cases, to analyze those variables in relation with early onset of BC, the manner of detection ...

    Abstract OBJECTIVE: To investigate the association between family history (FH) of neoplasia, gyneco-obstetric factors and breast cancer (BC) in a case--control study. In cases, to analyze those variables in relation with early onset of BC, the manner of detection (self-examination, prompted by pain, or casual), the size of tumor, and the elapsed time to seek medical attention. MATERIAL AND METHODS: Data from 151 prevalent BC cases and 235 age-matched controls were analyzed by multiple logistic regression, to assess the influence of BC risk factors. RESULTS: Ten per cent of patients and 1% of controls had first-degree relatives (FDR) with BC. Family history of FDR with BC (OR, 11.2; 95% CI 2.42-51.92) or with gastric or pancreatic cancer (OR, 17.7; 95% CI 2.2-142.6) was associated with BC risk. Breastfeeding at or under 25 years of age was protective against BC (OR, 0.40; 95% CI 0.24-0.66). The manner of tumor detection did not influence its size at the time of diagnosis. CONCLUSIONS: Our study confirms that FH of BC and/or of gastric or pancreatic carcinoma are risk factors for BC, while lactation at 25 years of age or earlier is protective.
    Keywords breast neoplasms ; risk factors ; Mexico ; Public aspects of medicine ; RA1-1270
    Subject code 610
    Language English
    Publishing date 2000-01-01T00:00:00Z
    Publisher Instituto Nacional de Salud Pública
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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