Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

Microfinance Institutions (MFIs) offers small loans with easy repayment system and till now these institutions have served millions of needy people around the globe. This study highlights the hurdles influence the smooth working and growth of Microfinance institution in Egypt. The structured interviews were conducted from the top and mid-level managers of MFI's. This study revealed that interest rate, political and economic conditions, corruption, customer outreach, competition and technology are the important elements for MFI's success. It is evident that lack of use of technology and less importance drawn on customer outreach programs are the main challenges of MFI's in Egypt. This study provides a roadmap for practitioners and strategic

Locking of the knee is a one of the commonest orthopedic outpatient presentation. This patient usually need magnetic resonance imaging (MRI) when there is suspected lesion in the soft tissue clinically. Meniscal tears is the first differential diagnosis when accompany with painful knee. (1, 2)Giant cell tumor (GCT) is benign a localized nodular tenosynovitis often occur in the tendon sheath , Mostly involve the hand tendons in middle age group between 30 and 50 years old , female affect more than male.(3,4) The WHO defines two well-known kinds of giant cell tumor: (1) pigmented villonodular synovitis ( generalized type), which mainly involve the joints of the lower limb and (2) giant cell tumor of the tendon sheath ( localized type)

Locking of the knee is a one of the commonest orthopedic outpatient presentation. This patient usually need magnetic resonance imaging (MRI) when there is suspected lesion in the soft tissue clinically. Meniscal tears is the first differential diagnosis when accompany with painful knee. (1, 2)
Giant cell tumor (GCT) is benign a localized nodular tenosynovitis often occur in the tendon sheath , Mostly involve the hand tendons in middle age group between 30 and 50 years old , female affect more than male.(3,4) The WHO defines two well-known kinds of giant cell tumor: (1) pigmented villonodular synovitis ( generalized type), which mainly involve the joints of the lower limb and (2) giant cell tumor of the tendon sheath ( localized type)

Massive multiple-input multiple-output (massive-MIMO) is considered as the key technology to meet the huge demands of data rates in the future wireless communications networks. However, for massive-MIMO systems to realize their maximum potential gain, sufficiently accurate downlink (DL) channel state information (CSI) with low overhead to meet the short coherence time (CT) is required. Therefore, this article aims to overcome the technical challenge of DL CSI estimation in a frequency-division-duplex (FDD) massive-MIMO with short CT considering five different physical correlation models. To this end, the statistical structure of the massive-MIMO channel, which is captured by the physical correlation is exploited to find sufficiently

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