A5041031733- Cutaneous Melanoma Detection and Management
- AI in cancer detection
- Glioma Diagnosis and Treatment
- Optical Coherence Tomography Applications
- Online and Blended Learning
- Digital Imaging for Blood Diseases
- Radiomics and Machine Learning in Medical Imaging
- Acne and Rosacea Treatments and Effects
- Meningioma and schwannoma management
- Water Quality Monitoring Technologies
- Brain Tumor Detection and Classification
- Infective Endocarditis Diagnosis and Management
- melanin and skin pigmentation
- Dermatology and Skin Diseases
- Cardiac Valve Diseases and Treatments
- EEG and Brain-Computer Interfaces
- Vascular Malformations Diagnosis and Treatment
- Workaholism, burnout, and well-being
- FinTech, Crowdfunding, Digital Finance
- Chronic Lymphocytic Leukemia Research
- Motor Control and Adaptation
- Ocular Oncology and Treatments
- Advancements in Transdermal Drug Delivery
- Work-Family Balance Challenges
- Meta-analysis and systematic reviews
University of Pittsburgh
2022-2024
University of Tikrit
2024
University of Nottingham
2019-2024
University of Pittsburgh Medical Center
2023-2024
Divisional Headquarters Teaching Hospital Mirpur
2024
UPMC Hillman Cancer Center
2023
Cornell University
2021-2022
Huashan Hospital
2020
Fudan University
2020
Shanghai Center for Brain Science and Brain-Inspired Technology
2020
Globally, skin diseases are the fourth leading cause of non-fatal disease burden. Both high and low-income countries suffer from this burden; indicates prevention should be prioritised. In research work, an intelligent diagnosis scheme is proposed for multi-class lesion classification. The implemented using a hybrid approach i.e. deep convolution neural network error-correcting output codes (ECOC) support vector machine (SVM). designed, tested to classify image into one five categories,...
Breast cancer is one of the leading cancers affecting women around world. The Computer-Aided Diagnosis (CAD) system a powerful tool to assist pathologists during process diagnosing cancer, which effectively identifies presence cancerous cells. A standard CAD includes processes pre-processing, feature extraction, selection and classification. In this paper, we propose an enhanced breast classification technique called Deep Learning eXtreme Gradient Boosting (DLXGB) on histopathology images...
Pathological diagnosis of glioma subtypes is essential for treatment planning and prognosis. Standard histological based on postoperative hematoxylin eosin stained slides by neuropathologists. With advancing artificial intelligence (AI), the aim this study was to determine whether deep learning can be applied classification.
Malignant melanoma is the deadliest form of skin cancer. In 2013 around 14,509 cases were found in United Kingdom and rate increasing ever since. Melanoma can be easily treatable if detected early stages. Clinical as well automated methods are being used for diagnosis. Image-based computer aided diagnosis systems have great potential malignant detection. this paper we review state art system examine recent practices different steps these systems. Statistics results from most important...
Skin diseases are the 4th leading cause of skin burden worldwide. Computer-aided diagnosis (CAD) systems have been developed to lessen this and help patients conduct early assessment lesion. Mostly CAD available in literature only provide cancer classification. Classification lesion is a challenging research area due similar characteristics lesions. A novel system presented work for most common lesions (acne, eczema, psoriasis, benign malignant melanoma). The proposed approach based on...
Skin diseases cases are increasing on a daily basis and difficult to handle due the global imbalance between skin disease patients dermatologists. among top 5 leading cause of worldwide burden. To reduce this burden, computer-aided diagnosis systems (CAD) highly demanded. Single classification is major shortcoming in existing work. Due similar characteristics diseases, multiple lesions very challenging. This research work an extension our where novel scheme proposed for multi-class...
This research work is aimed at investing skin lesions classification problem using Convolution Neural Network (CNN) cloud-server architecture. Using the cloud services and CNN, a real-time mobile-enabled expert system “i-Rash” proposed developed. i-Rash early diagnosis of acne, eczema psoriasis remote locations. The model used in developed CNN “SqueezeNet”. transfer learning approach for training trained tested on 1856 images. benefit SqueezeNet results limited size i.e. only 3 MB. For...
Overconsumption of resources is a global issue. To deal with resource depletion and mitigate impending crises, the circular economy (CE) solution provides an ecosystem by reducing waste via reuse, repair, refurbishment, recycling existing materials products. However, as complexity supply chains increasing effective CE management very crucial. We want to address this issue performing feasibility study AI-enabled blockchain technology using our developed customised NFT platform, TrackGenesis...
Treatment guidelines in neurosurgery are often based on evidence obtained from randomized controlled trials (RCTs).To evaluate the robustness of RCTs supporting current central nervous tumor and cerebrovascular disease by calculating their fragility index (FI)-the minimum number patients needed to switch an event nonevent outcome change significant trial primary outcome.We analyzed referenced Congress Neurological Surgeons American Association management. Trial characteristics, finding a...
Illness directly affecting the skin is fourth most frequent cause of all human disease, and seeking attention researchers. In this research work, one such effort made by proposing a mobile-enabled expert system named "i-Rash" for classification inflammatory lesions. i-Rash can classify image into four non-overlapping classes, i.e. healthy, acne, eczema, psoriasis. The model trained using deep learning SqueezeNet. pre-trained SqueezeNet re-trained on dataset transfer approach. tested 1856...
Pakistan as culturally diverse country possesses wide range of cultural factors. These factors affect the living style, traditions, values and norms well education. As e-learning is global mode education so learners from different backgrounds enrolled in learning management system. Diversity culture styles should keep under considerations while designing environment. In this research work e highlighted by Bentley ET. AL are incorporated to find learner level. After assignment level,...
Drug-resistant focal epilepsy is the failure of antiepileptic drugs scheduled to obtain epileptic free brain activities. In human brain, cerebral hemispheres are most commonly involved regions in epilepsy. case failure, surgical treatment best cure possible. However, correct localization epileptogenic region a challenging task for neurologists, while computer scientists, automatic is. This research work’s aim explore functional activities all drug-resistant patients and achieve high accuracy...
Rapid development of Internet and information technologies has gifted us with a new diverse mode learning known as e-learning. In the current era, e-learning made rapid, influential, universal, interactive, vibrant, economic development. Now become global education. E-learning means use internet, computer communications to acquire Learners social, cultural, economic, linguistic, religious backgrounds from all over world are taking benefits e-learning, culture target learners plays vital role...
Hürthle cell carcinoma (HCC) is an unusual and aggressive variant of the follicular type differentiated thyroid cancer (DTC), accounting for less than 3% DTCs but posing highest risk metastasis. Brain metastases are uncommonly reported in literature pose a poor prognosis. The low rate brain from HCC coupled with ambiguous treatment protocols extracranial disease complicate successful management definitive strategy. authors present case patient metastasis to skull base, cortex, spine recent...