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A Scoring System to Assess Patients with Diabetes: nutech Functional Score

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Journal of Diabetes Mellitus 2015年第4期5卷 245-251页

作者： Geeta Shroff Director and Founder Nutech Mediworld New Delhi India

Background: Diabetes mellitus (DM) is a metabolic disorder characterized by hyperglycemia. The symptoms of hyperglycemia include polyuria, polydypsia, polyphagia, blurred vision and weight loss. Various diagnostic tests are used for the diagnosis of DM in patients, but the findings of these tests cannot be assumed to be completely valid. This study aimed at developing a novel scoring system to assess the patients suffering from DM. Method: We assessed the patients based on various diagnostic tests available for DM and prepared a single list of these tests. The tests were categorized and graded based on the World Health Organization (WHO) criteria. Further, we coverted the grades into numeric values for easy use. Results: NFS for diabetes is an 11-point scoring system that assesses the patient’s condition before and after therapy. To facilitate the conduct of probability based studies, we have converted the scores into numeric values in the range of (0, 1). Each symptom is graded as (1, 2, 3, 4, 5) that runs in BAD → GOOD direction. Conclusion: NFS is a beneficial scoring system that can be used worldwide to assess the patients with DM.

关键词： Diabetes Mellitus nutech Functional Score (NFS) Scoring System Diagnosis

Therapeutic potential of human embryonic stem cells in type 2 diabetes mellitus

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World Journal of Stem Cells 2016年第7期8卷 223-230页

作者： Geeta Shroff nutech Mediworld New Delhi 110016 India

AIM:To evaluate the safety and efficacy of human embryonic stem cells(h ESCs)for the management of type 2 diabetes mellitus(T2DM).METHODS:Patients with a previous history of diabetes and its associated complications were enrolled and injected with hE SC lines as per the defined *** patients were assessed using nutech functional score(NFS),a numeric scoring scale to evaluate the patients for 11 diagnostic *** were evaluated at baseline and at the end of treatment period 1(T1).All the parameters were graded on the NFS scale from 1to *** possible grade(HPG)of 5 was considered as the grade of best ***:Overall,94.8%of the patients showed improvement by at least one grade of NFS at the end of *** all the 11 parameters evaluated,54%of patients achieved HPG after *** four essential parameters(improvement in glycated hemoglobin(HbA 1c)and insulin level,and fall in number of other oral hypoglycemic drugs with and without insulin)are presented in *** Hb A1c,72.6%of patients at the end of T1 met the World Health Organization cut off value,i.e.,6.5%of HbA *** insulin level,65.9%of patients at the end of T1 were able to achieve *** treatment,the improvement was seen in 16.3%of patients who required no more than two medications along with ***,21.5%of patients were improved as their dosage regimen for using oral drugs was reduced to 1-2 from ***:hE SC therapy is beneficial in patients with diabetes and helps in reducing their dependence on insulin and other medicines.

关键词： Type 2 diabetes mellitus Human embryonic stem cells Insulin Glycated hemoglobin nutech functional scoring scale

Morphogenesis of human embryonic stem cells into mature neurons under in vitro culture conditions

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World Journal of Experimental Medicine 2016年第4期6卷 72-79页

作者： Geeta Shroff nutech Mediworld

AIM To describe the morphogenesis of different neuronal cells from the human embryonic stem cell(h ESC) line,SCT-N,under in vitro culture *** The directed neuronal cell line was produced from a single,spare,pre-implantation stage fertilized ovum that was obtained during a natural in vitro fertilization process. The h ESCs were cultured and maintained as per our proprietary in-house technology in a Good Manufacturing Practice,Good Laboratory Practice and Good Tissue Practice compliant laboratory. The cell line was derived and incubated in aerobic conditions. The cells were examined daily under a phase contrast microscope for their growth and differentiation. RESULTS Different neural progenitor cells(NPCs) and differentiating neurons were observed under the culture conditions. Multipotent NPCs differentiated into all three types of nervous system cells,i.e.,neurons,oligodendrocytes and astrocytes. Small projections resembling neurites or dendrites,and protrusion coming out of the cells,were observed. Differentiating cells were observed at day 18 to 20. The differentiating neurons,neuronal bodies,axons,and neuronal tissue were observed on day 21 and day 30 of the culture. On day 25 and day 30,prominent neurons,axons and neuronal tissue were observed under phase contrast microscopy. 4',6-diamidino-2-phenylindole staining also indicated the pattern of differentiating neurons,axonal structure and neuronal tissue. CONCLUSION This study describes the generation of different neuronal cells from an h ESC line derived from biopsy of blastomeres at the two-cell cleavage stage from a discarded embryo.

关键词： Human embryonic stem cells Multipotency Neural differentiation Neural progenitor cells In-vitro fertilization

A Functional Scoring System to Assess the Level of Impairment in Patients with Low Vision Impairment

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Open Journal of Ophthalmology 2017年第3期7卷 204-215页

作者： Geeta Shroff nutech Mediworld New Delhi India

Background: Low vision is referred to as visual impairment (VI) if it is not cured through surgery, drugs, spectacles or contact lenses. It interferes with day-to-day living activities and is associated with the major eye blinding diseases. Numerous tests are used to carry out diagnosis of VI, but their outcomes are unreliable. Objective: To develop a functional scoring system, for accessing the ailment of patients with VI based on observations and clinical symptoms. Methods and Findings: We prepared the list of all possible symptoms that were associated with low vision. Based on this list, we established a scoring system, nutech Functional Score (NFS), which is a 33-point positional and directional scoring system that evaluates the patient with VI. The scores have been converted into numeric values for conducting probability based studies. All the symptoms are graded between 1 to 5 that runs in BAD → GOOD direction. Conclusion: NFS is a distinctive tool that can be used globally to evaluate the patients with low vision.

关键词： nutech Functional Score (NFS) Visual Impairment Cortical Visual Impairment (CVI) Positional Scoring System Ocular Visual Impairment (OVI)

Use of Human Embryonic Stem Cells in the Treatment of Diabetes Mellitus: A Case Series

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Journal of Diabetes Mellitus 2015年第4期5卷 313-318页

作者： Geeta Shroff nutech Mediworld New Delhi India

Introduction: Diabetes mellitus (DM), a metabolic disorder, is known to be highly prevalent in people aged 40 - 60 years in developing countries whereas in developed countries, it mostly affects people above the age of 60 years. It is of two types: DM type I, an autoimmune disorder that mostly onsets after an infection and DM type II that is commonly associated with obesity. Several treatments are available for the treatment of DM, but none has successfully cured diabetes. Nowadays, stem cell therapy is being investigated for use in the treatment of DM and has shown positive results. Case Report: Our study presented results of three diabetic patients who were treated with human embryonic stem cell (hESC) therapy. Following the therapy, blood glucose levels were reduced. An improvement was observed in eye sight, stamina, gait pattern endurance, mental focus ability and muscle strength. There was a reduction in secondary side effects of high blood sugar such as affectation of cardiac, kidneys, polyneuropathy, vision etc. No adverse events and teratoma formation were observed after the treatment. Conclusion: It was concluded that hESCs showed good therapeutic potential in the treatment of patients with diabetes.

关键词： Diabetes hESC Therapy iPSCs

Fruits and Vegetable Diseases Recognition Using Convolutional Neural Networks

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Computers, Materials & Continua 2022年第1期70卷 619-635页

作者： Javaria Amin Muhammad Almas Anjum Muhammad Sharif Seifedine Kadry Yunyoung Nam University of Wah WahCanttPakistan National University of Technology(nutech) IJP RoadIslamabadPakistan COMSATS University Islamabad Wah CampusPakistan Faculty of Applied Computing and Technology Noroff University CollegeKristiansandNorway Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea

As they have nutritional,therapeutic,so values,plants were regarded as important and they’re the main source of humankind’s energy *** pathogens will affect its leaves at a certain time during crop cultivation,leading to substantial harm to crop productivity&economic selling *** the agriculture industry,the identification of fungal diseases plays a vital ***,it requires immense labor,greater planning time,and extensive knowledge of plant *** approaches are developed and tested by different researchers to classify plant disease identification,and that in many cases they have also had important results several ***,the proposed study presents a new framework for the recognition of fruits and vegetable *** work comprises of the two phases wherein the phase-I improved localization model is presented that comprises of the two different types of the deep learning models such asYouOnly Look Once(YOLO)v2 and Open Exchange Neural(ONNX)*** localizationmodel is constructed by the combination of the deep features that are extracted from the ONNX model and features learning has been done through the convolutional-05 layer and transferred as input to the YOLOv2 *** localized images passed as input to classify the different types of plant *** classification model is constructed by ensembling the deep features learning,where features are extracted dimension of 1×1000 from pre-trained Efficientnetb0 model and supplied to next 07 layers of the convolutional neural network such as 01 features input,01 ReLU,01 Batch-normalization,02 *** proposed model classifies the plant input images into associated labels with approximately 95%prediction scores that are far better as compared to current published work in this domain.

关键词： Efficientnetb0 open exchange neural network features learning softmax YOLOv2

3D Semantic Deep Learning Networks for Leukemia Detection

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Computers, Materials & Continua 2021年第10期69卷 785-799页

作者： Javaria Amin Muhammad Sharif Muhammad Almas Anjum Ayesha Siddiqa Seifedine Kadry Yunyoung Nam Mudassar Raza University of Wah Wah CanttPakistan COMSATS University Islamabad Wah CampusPakistan National University of Technology(nutech) IJP Road IslamabadPakistan Faculty of Applied Computing and Technology Noroff University CollegeKristiansandNorway Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea

White blood cells(WBCs)are a vital part of the immune system that protect the body from different types of bacteria and *** cell growth destroys the body’s immune system,and computerized methods play a vital role in detecting abnormalities at the initial *** this research,a deep learning technique is proposed for the detection of *** proposed methodology consists of three *** I uses an open neural network exchange(ONNX)and YOLOv2 to localize *** localized images are passed to Phase II,in which 3D-segmentation is performed using deeplabv3 as a base network of the pre-trained Xception *** segmented images are used in Phase III,in which features are extracted using the darknet-53 model and optimized using Bhattacharyya separately criteria to classify *** proposed methodology is validated on three publically available benchmark datasets,namely ALL-IDB1,ALL-IDB2,and LISC,in terms of different metrics,such as precision,accuracy,sensitivity,and dice *** results of the proposed method are comparable to those of recent existing methodologies,thus proving its effectiveness.

关键词： YOLOv2 darknet53 Bhattacharyya separately criteria ONNX

Malaria Parasite Detection Using a Quantum-Convolutional Network

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Computers, Materials & Continua 2022年第3期70卷 6023-6039页

作者： Javaria Amin Muhammad Almas Anjum Abida Sharif Mudassar Raza Seifedine Kadry Yunyoung Nam University of Wah Wah CanttPakistan National University of Technology(nutech) IslamabadPakistan COMSATS University Islamabad Vehari CampusVehariPakistan COMSATS University Islamabad Wah CampusPakistan Faculty of Applied Computing and Technology Noroff University CollegeKristiansandNorway Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea

Malaria is a severe illness triggered by parasites that spreads via mosquito *** underdeveloped nations,malaria is one of the top causes of mortality,and it is mainly diagnosed through ***-assisted malaria diagnosis is difficult owing to the fine-grained differences throughout the presentation of some uninfected and infected ***,in this study,we present a new idea based on the ensemble quantum-classical framework for malaria *** methods comprise three core steps:localization,segmentation,and *** the first core step,an improved FRCNN model is proposed for the localization of the infected malaria ***,the RGB localized images were converted into YCbCr channels to normalize the image intensity ***,the actual lesion region was segmented using a histogram-based color thresholding *** segmented images were employed for classification in two different *** the first method,a CNN model is developed by the selection of optimum layers after extensive experimentation,and the final computed feature vector is passed to the softmax layer for classification of the infection/non-infection of themicroscopicmalaria ***,a quantum-convolutionalmodel is employed for informative feature extraction from microscopicmalaria images,and the extracted feature vectors are supplied to the softmax layer for ***,classification results were analyzed from two different models and concluded that the quantum-convolutional model achieved maximum accuracy as compared to *** proposed models attain a precision rate greater than 90%,thereby proving that these models performed better than the existing models.

关键词： Quantum convolutional RGB YCbCr histogram Malaria

Convolutional Bi-LSTM Based Human Gait Recognition Using Video Sequences

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Computers, Materials & Continua 2021年第8期68卷 2693-2709页

作者： Javaria Amin Muhammad Almas Anjum Muhammad Sharif Seifedine Kadry Yunyoung Nam ShuiHua Wang University of Wah Wah Cantt47040Pakistan National University of Technology(nutech) Islamabad44000Pakistan COMSATS University Islamabad Wah CampusWah CanttPakistan Faculty of Applied Computing and Technology Noroff University CollegeKristiansandNorway Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea Department of Mathematics University of LeicesterLeicesterUK

Recognition of human gait is a difficult assignment,particularly for unobtrusive surveillance in a video and human identification from a large ***,a method is proposed for the classification and recognition of different types of human *** proposed approach is consisting of two *** phase I,the new model is proposed named convolutional bidirectional long short-term memory(Conv-BiLSTM)to classify the video frames of human *** this model,features are derived through convolutional neural network(CNN)named ResNet-18 and supplied as an input to the LSTM model that provided more distinguishable temporal *** phase II,the YOLOv2-squeezeNet model is designed,where deep features are extricated using the fireconcat-02 layer and fed/passed to the tinyYOLOv2 model for recognized/localized the human gaits with predicted *** proposed method achieved up to 90%correct prediction scores on CASIA-A,CASIA-B,and the CASIA-C benchmark *** proposed method achieved better/improved prediction scores as compared to the recent existing works.

关键词： Bi-LSTM YOLOv2 open neural network resNet-18 gait squeezeNet