scholarly journals CAT-CAD: A Computer-Aided Diagnosis Tool for Cataplexy

Computers ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 51
Author(s):  
Ilaria Bartolini ◽  
Andrea Di Luzio

Narcolepsy with cataplexy is a severe lifelong disorder characterized, among others, by sudden loss of bilateral face muscle tone triggered by emotions (cataplexy). A recent approach for the diagnosis of the disease is based on a completely manual analysis of video recordings of patients undergoing emotional stimulation made on-site by medical specialists, looking for specific facial behavior motor phenomena. We present here the CAT-CAD tool for automatic detection of cataplexy symptoms, with the double aim of (1) supporting neurologists in the diagnosis/monitoring of the disease and (2) facilitating the experience of patients, allowing them to conduct video recordings at home. CAT-CAD includes a front-end medical interface (for the playback/inspection of patient recordings and the retrieval of videos relevant to the one currently played) and a back-end AI-based video analyzer (able to automatically detect the presence of disease symptoms in the patient recording). Analysis of patients’ videos for discovering disease symptoms is based on the detection of facial landmarks, and an alternative implementation of the video analyzer, exploiting deep-learning techniques, is introduced. Performance of both approaches is experimentally evaluated using a benchmark of real patients’ recordings, demonstrating the effectiveness of the proposed solutions.

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Aysen Degerli ◽  
Mete Ahishali ◽  
Mehmet Yamac ◽  
Serkan Kiranyaz ◽  
Muhammad E. H. Chowdhury ◽  
...  

AbstractComputer-aided diagnosis has become a necessity for accurate and immediate coronavirus disease 2019 (COVID-19) detection to aid treatment and prevent the spread of the virus. Numerous studies have proposed to use Deep Learning techniques for COVID-19 diagnosis. However, they have used very limited chest X-ray (CXR) image repositories for evaluation with a small number, a few hundreds, of COVID-19 samples. Moreover, these methods can neither localize nor grade the severity of COVID-19 infection. For this purpose, recent studies proposed to explore the activation maps of deep networks. However, they remain inaccurate for localizing the actual infestation making them unreliable for clinical use. This study proposes a novel method for the joint localization, severity grading, and detection of COVID-19 from CXR images by generating the so-called infection maps. To accomplish this, we have compiled the largest dataset with 119,316 CXR images including 2951 COVID-19 samples, where the annotation of the ground-truth segmentation masks is performed on CXRs by a novel collaborative human–machine approach. Furthermore, we publicly release the first CXR dataset with the ground-truth segmentation masks of the COVID-19 infected regions. A detailed set of experiments show that state-of-the-art segmentation networks can learn to localize COVID-19 infection with an F1-score of 83.20%, which is significantly superior to the activation maps created by the previous methods. Finally, the proposed approach achieved a COVID-19 detection performance with 94.96% sensitivity and 99.88% specificity.


1980 ◽  
Vol 25 (5) ◽  
pp. 381-385
Author(s):  
Jean-Charles Crombez

The questionnaire on continuing education by the Canadian Psychiatric Association's Council on Education and Professional Liaison, sent in 1978 to all Canadian psychiatrists, raises in the author's mind, in spite of his participation in its establishment, the question of the philosophy behind it. Indeed, seeing signs of a greater problem, he identifies the need for two studies, one dealing with the “object”, the other with the “relationship”. Not elaborating on the first one (description of patients and techniques) which is well known, he describes the second as the knowledge and significance of the encounter (that of two persons inevitably and structurally linked). This “area of relations” paradoxically given too little value in the teaching of psychiatry, is more analogical than logical, more intuitive than deductive, more perceptual than intellectual, and more multifactorial than linear. Yet, this dimension of the encounter (whether individual, familial, group or co-therapy) should take place in conjunction with the objective approach, but the latter occurs alone too often. In order to give to this field of relationship a scientific status of its own, and to reintroduce the techniques instead of using them as guard-rails, proper techniques or methods should be employed or developed if necessary. This includes on the one hand the learning of different levels of awareness and the widening of our perceptual, sensorial, intuitive and analogical capacities. (This would allow for an experience of the fundamental relationship between fields that are apart symptom-wise: dream and awakening, physical and psychic, interior and exterior, fantasy and reality, representations and objects, and so on.) On the other hand this leads us to increase our capacity to listen, to abandon ourselves and to get involved, and to “conceive” a presence within the relationship. Finally, there is this learning of how to observe oneself in a situation, of how to look at what is going on within the encounter (and it is in that very position and this very questioning that the concept of neutrality can be understood, not in the legendary phlegm of impenetrability). This can be done within an “experiential” teaching: for the therapist this means the experience and the study of his own involvement, either with a patient or in groups. Another method is supervision, not as “super”-vision but rather as “inter-discovery” and not as control but rather as “ex-pression.” Working in small groups with colleagues where one can enquire about others’ experiences without any normative goal and with an open attitude is desirable. Another tool would be professional meetings, but not in their current form which is not adapted to the field of the relationship. And so on. The author sees a fundamental necessity for these two fields of the “object” and the “relationship” to be taught conjointly, and neither one nor the other to be excluded from the psychiatrist's training; which is not the case at present. The “field of the object” implies an effort at objectifying, defining variables, causes, using experimental methodology, and a more quantitative analysis. The “field of the relationship” implies positions that are often opposed to this. This contradiction seems necessary and inevitable within every person. One tendency is to make ourselves believe that we avoid this contradiction by pretending to total objectivity: that of scientific psychiatry and clear logic. Finally the author returns to the questionnaire that, precisely in its form, is too uniquely meant for an objective teaching: teaching of diagnoses, illnesses, chart controls, patient controls, teaching through questionnaires, case presentations, putting emphasis on articles or textbooks. This proposed method is adapted for teaching persons considered as entities; and learning techniques considered as reified tools. This is exactly the classical stream of university courses and specialty examinations. This reinforces the illusion. There is also the danger, via the “credit” game, that it will strengthen the already strong tendency to mere objectifying of the subject, of the therapist and of science; that it will privilege a normative vision; and discredit certain essential and humanistic dimensions.


Author(s):  
Bosede Iyiade Edwards ◽  
Nosiba Hisham Osman Khougali ◽  
Adrian David Cheok

With recent focus on deep neural network architectures for development of algorithms for computer-aided diagnosis (CAD), we provide a review of studies within the last 3 years (2015-2017) reported in selected top journals and conferences. 29 studies that met our inclusion criteria were reviewed to identify trends in this field and to inform future development. Studies have focused mostly on cancer-related diseases within internal medicine while diseases within gender-/age-focused fields like gynaecology/pediatrics have not received much focus. All reviewed studies employed image datasets, mostly sourced from publicly available databases (55.2%) and few based on data from human subjects (31%) and non-medical datasets (13.8%), while CNN architecture was employed in most (70%) of the studies. Confirmation of the effect of data manipulation on quality of output and adoption of multi-class rather than binary classification also require more focus. Future studies should leverage collaborations with medical experts to aid future with actual clinical testing with reporting based on some generally applicable index to enable comparison. Our next steps on plans for CAD development for osteoarthritis (OA), with plans to consider multi-class classification and comparison across deep learning approaches and unsupervised architectures were also highlighted.


2021 ◽  
Vol 1 (1) ◽  
pp. 45-54
Author(s):  
Neneng Samrotul Fuadah ◽  
Dedi Heryadi ◽  
Winarti Dwi Febriani

Abstract: This research is motivated by the low understanding of students in describing objects, the low understanding of the use of punctuation points and commas and the lack of continuity of one sentence with another. In the Indonesian language learning process, various learning techniques are needed, therefore the Scaffolding learning technique is expected to give effectiveness to the learning outcomes of students. In general, the Scaffolding technique is used to involve students taking an active and independent role in doing the given task. The purpose of this research was carried out to describe the effectiveness of the Scaffolding technique in Indonesian language description learning and learning outcomes using the Scaffolding technique. The location of this research is SDN 3 Sukamanah, Cipedes District, Tasikmalaya City. The sampling technique used was saturated sampling. The data collection used was the observation sheet and the pretest and posttest question writing instruments descriptions. The results of this study are that the average pretest value is 51.76 and the average posttest score is 83.10. Based on the N-gain test using the One Sample T-Test produces a sig value. (2-tailed) of 0,000 in accordance with the sig value testing criteria. (2-tailed) <0.05, then Ha is accepted. The conclusion of this study is that there is a significant effectiveness of using Scaffolding techniques on the learning outcomes of writing descriptions in Indonesian.Keywords: Scaffolding; Learning; Description Text.  Abstrak: Penelitian ini bertujuan untuk mengetahui efektivitas teknik Scaffolding pada pembelajaran menulis teks deskripsi dan prestasi belajar siswa. Pada umumnya teknik Scaffolding digunakan untuk melibatkan peserta didik perperan aktif dan mandiri dalam mengerjakan tugas yang diberikan. Tujuan dilaksanakan penelitian ini untuk mendeskripsikan keefektifan teknik Scaffolding pada pembelajaran deskripsi bahasa Indonesia dan hasil pembelajaran menggunakan teknik Scaffolding. Lokasi penelitian ini di SDN 3 Sukamanah Kecamatan Cipedes Kota Tasikmalaya. Teknik pengambilan sampel yang digunakan adalah sampling jenuh. Pengumpulan data yang digunakan adalah lembar observasi dan instrumen soal pretest dan posttest menulis deskripsi. Hasil penelitian ini adalah di dapat rata-rata nilai pretest 51,76 dan rata-rata nilai posttest 83,10. Berdasarkan uji N-gain menggunakan One Sampel T-Test menghasilkan nilai sig. (2-tailed) sebesar 0,000 sesuai dengan kriteria pengujian nilai sig. (2-tailed) < 0,05, maka Ha diterima. Kesimpulan penelitian ini adalah terdapat keefektifan yang signifikan penggunaan teknik Scaffolding pada hasil pembelajaran menulis deskripsi bahasa Indonesia.Kata Kunci: Scaffolding; Pembelajaran; Teks Deskripsi.


Author(s):  
Shashidhara Bola

A new method is proposed to classify the lung nodules as benign and malignant. The method is based on analysis of lung nodule shape, contour, and texture for better classification. The data set consists of 39 lung nodules of 39 patients which contain 19 benign and 20 malignant nodules. Lung regions are segmented based on morphological operators and lung nodules are detected based on shape and area features. The proposed algorithm was tested on LIDC (lung image database consortium) datasets and the results were found to be satisfactory. The performance of the method for distinction between benign and malignant was evaluated by the use of receiver operating characteristic (ROC) analysis. The method achieved area under the ROC curve was 0.903 which reduces the false positive rate.


Author(s):  
Todor D. Ganchev

In this chapter we review various computational models of locally recurrent neurons and deliberate the architecture of some archetypal locally recurrent neural networks (LRNNs) that are based on them. Generalizations of these structures are discussed as well. Furthermore, we point at a number of realworld applications of LRNNs that have been reported in past and recent publications. These applications involve classification or prediction of temporal sequences, discovering and modeling of spatial and temporal correlations, process identification and control, etc. Validation experiments reported in these developments provide evidence that locally recurrent architectures are capable of identifying and exploiting temporal and spatial correlations (i.e., the context in which events occur), which is the main reason for their advantageous performance when compared with the one of their non-recurrent counterparts or other reasonable machine learning techniques.


2019 ◽  
Vol 624 ◽  
pp. A45 ◽  
Author(s):  
Y. Alibert

Context. Planet formation models now often consider the formation of planetary systems with more than one planet per system. This raises the question of how to represent planetary systems in a convenient way (e.g. for visualisation purpose) and how to define the similarity between two planetary systems, for example to compare models and observations. Aims. We define a new metric to infer the similarity between two planetary systems, based on the properties of planets that belong to these systems. We then compare the similarity of planetary systems with the similarity of protoplanetary discs in which they form. Methods. We first define a new metric based on mixture of Gaussians, and then use this metric to apply a dimensionality reduction technique in order to represent planetary systems (which should be represented in a high-dimensional space) in a two-dimensional space. This allows us study the structure of a population of planetary systems and its relation with the characteristics of protoplanetary discs in which planetary systems form. Results. We show that the new metric can help to find the underlying structure of populations of planetary systems. In addition, the similarity between planetary systems, as defined in this paper, is correlated with the similarity between the protoplanetary discs in which these systems form. We finally compare the distribution of inter-system distances for a set of observed exoplanets with the distributions obtained from two models: a population synthesis model and a model where planetary systems are constructed by randomly picking synthetic planets. The observed distribution is shown to be closer to the one derived from the population synthesis model than from the random systems. Conclusions. The new metric can be used in a variety of unsupervised machine learning techniques, such as dimensionality reduction and clustering, to understand the results of simulations and compare them with the properties of observed planetary systems.


2020 ◽  
Vol 12 (4) ◽  
pp. 1606 ◽  
Author(s):  
Vincenzo Barrile ◽  
Antonino Fotia ◽  
Giovanni Leonardi ◽  
Raffaele Pucinotti

Structural Health Monitoring (SHM) allows us to have information about the structure under investigation and thus to create analytical models for the assessment of its state or structural behavior. Exceeded a predetermined danger threshold, the possibility of an early warning would allow us, on the one hand, to suspend risky activities and, on the other, to reduce maintenance costs. The system proposed in this paper represents an integration of multiple traditional systems that integrate data of a different nature (used in the preventive phase to define the various behavior scenarios on the structural model), and then reworking them through machine learning techniques, in order to obtain values to compare with limit thresholds. The risk level depends on several variables, specifically, the paper wants to evaluate the possibility of predicting the structure behavior monitoring only displacement data, transmitted through an experimental transmission control unit. In order to monitor and to make our cities more “sustainable”, the paper describes some tests on road infrastructure, in this contest through the combination of geomatics techniques and soft computing.


Author(s):  
Jon D. Fricker ◽  
Yunchang Zhang

A large number of crosswalks are indicated by pavement markings and signs, but are not signal-controlled. In this paper, such a location is called “semi-controlled.” At locations where such a crosswalk has moderate amounts of pedestrian and vehicle traffic, pedestrians and motorists often engage in a non-verbal “negotiation” to determine who should proceed first. This paper describes the detailed analysis of video recordings of more than 3,400 pedestrian–motorist interactions at semi-controlled crosswalks. The study also took advantage of a conversion from one-way operation in spring 2017 to two-way operation in spring 2018 on the street chosen for data collection and analysis. This permitted before and after studies at the same location. The pedestrian models used mixed effects logistic regression and binary logistic regression to identify factors that influence the likelihood of a pedestrian crossing under specified conditions. The complementary motorist models used generalized ordered logistic regression to identify factors that impact a driver’s likelihood of decelerating, which was found to be a more useful factor than likelihood of yielding to pedestrian. The data showed that 56.5% of drivers slowed down or stopped for pedestrians on the one-way street. This value rose to 63.9% on the same street after it had been converted to two-way operation. Moreover, two-way operation eliminated the effects of the presence of other vehicles on driver behavior. Relationships were found that can lead to policies and control strategies designed to improve the operation of such a crosswalk.


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