Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision based on the fusion of probabilities. Individually, the classifier based on PI achieved 93.1% accuracy, whereas the deep classifiers reached classification accuracies over 90% only in isolated cases. Overall, the average accuracy of the deep networks over the four corneal maps ranged from 86% (SfN) to 89.9% (AN). The classifier ensemble increased the accuracy of the deep classifiers based on corneal maps to values ranging (92.2% to 93.1%) for SqN and (93.1% to 94.8%) for AN. Including in the ensemble-specific combinations of corneal maps’ classifiers and PI increased the accuracy to 98.3%. Moreover, visualization of first learner filters in the networks and Grad-CAMs confirmed that the networks had learned relevant clinical features. This study shows the potential of creating ensembles of deep classifiers fine-tuned with a transfer learning strategy as it resulted in an improved accuracy while showing learnable filters and Grad-CAMs that agree with clinical knowledge. This is a step further towards the potential clinical deployment of an improved computer-assisted diagnosis system for KCN detection to help ophthalmologists to confirm the clinical decision and to perform fast and accurate KCN treatment.
Flow-production systems whose pieces are connected in a row may not have maintenance scheduling procedures fixed because problems occur at different times (electricity plants, cement plants, water desalination plants). Contemporary software and artificial intelligence (AI) technologies are used to fulfill the research objectives by developing a predictive maintenance program. The data of the fifth thermal unit of the power station for the electricity of Al Dora/Baghdad are used in this study. Three stages of research were conducted. First, missing data without temporal sequences were processed. The data were filled using time series hour after hour and the times were filled as system working hours, making the volume of the data relativel
... Show MoreThe measurement data of the raw water quality of Tigris River were statistically analyzed to measure the salinity value in relation to the selected raw water quality parameters. The analyzed data were collected from five water treatment plants (WTPs) assembled alongside of the Tigris River in Baghdad: Al-Karkh, Al-Karama, Al-Qadisiya, Al-Dora, and Al-Wihda for the period from 2015 to 2021. The selected parameters are total dissolved solid (TDS), electrical conductivity (EC), pH and temperature. The main objective of this research is to predicate a mathematical model using SPSS software to calculate the value of salinity along the river, in addition, the effect of electrical conductivi
The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T
... Show MoreThe research aims to identify how to enhance the quality of the human resources, focusing on four dimensions (efficiency, effectiveness, flexibility, and reliability), by adopting an adventure learning method that combines theoretical and applied aspects at the same time, when developing human resources and is applied using information technology, and that Through its dimensions, which are (cooperation, interaction, communication, and understanding), as the research problem indicated a clear deficiency in the cognitive perception of the mechanism of employing adventure learning dimensions in enhancing human resources quality, so the importance of research was to present treatments and proposals to reduce this problem. To achieve
... Show MoreWireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s
... Show MoreThe study aims to identify the level of cognitive beliefs, as well as to identify the level of self-organized learning strategies among intermediate school students. The study also aims to identify the differences in the level of self-organized learning strategies among intermediate school students in term of gender, branch (scientific, literary). In order to achieve the research objectives, the researcher designed a scale to measure the cognitive beliefs. As for the scale of self-organized learning strategies, the researcher adopted a scale of (Pintrich et al. 1991), which was translated by (Izzat Abdelhamid, 1999) , For self-organized learning strategies, the sample consisted of (400) students from the research population, whic
... Show MoreUnter dem Titel " Technische Methoden im Fremdsprachunterricht als eine neueste Methode im Fremdsprachlernen, die Spiele als Muster"
versteht man, dass die Forschung sich mit einer neuen Methoden im Fremdsprachunterricht beschäftigt. Von den neuen Methoden im Unterricht sind die Spiele. So man sieht in den letzten Jahren viele Artikel zum Thema Spiele im Fremdsprschunterricht. Davon gehen wir aus, dass die Spiele im Unterricht eine groβe Rolle spielt, denn diese Methode macht Lust, Spaβ im Lernenprozeβ. Die Spiele im Unterricht bezeichnen als ein Mittel, um Unterricht etwas Schönes , Nützliches und Lebendigs zu sein. Die Spiele sind vielfälltig und unterscheidet sich nach den Themen und Materialien. In dieser F
... Show MoreFor aspirin estimated, a molecularly imprinted polymer MIP-ASP electrodes were generated by electro-polymerization process, the electrodes were prepared by combining the template (aspirin) with (vinyl acetate (VA), 1-vinylimidizole (VIZ) as a functional monomer and N, N-methylene bisacrylamide (MBAA) as crosslinkers using benzoyl peroxide (BPO) as an initiator. The efficiency of the membrane electrodes was analyzed by differential pulse voltammetry (DPV). Four electrodes were synthesized using two different plasticizers, di-butyl sebacate (DBS), di-octyl phthalate (DOP) in PVC matrix. Scanning electron microscopy (SEM) was used to describe the generated MIP, studying the electrodes properties, the slope, detection limit, and life
... Show MoreIn this research, a number of the western al-Anbar clays (red iron clays, Attapulgite) were modified by treating them thermally with a temperature of 650oC. After that, these clays reflux with sodium hydroxide 5% for 1 hour by using microwave as a power supply. The research included fractionation alqayaira crude oil the fractionation included removing the asphaltene by precipitation from the crude using a simple paraffin solvent (normal hexane) as a non-soluble substance. After that it was filtered using the ash-free filter paper 42, the dissolved part, maltinate, was taken, drying a temperature of 75oC and weight, and to find the percentage of the two parts. Malatine was divided into three main parts (paraf
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