Brain tumor segmentation and classification on MRI via deep hybrid representation learning

N Farajzadeh, N Sadeghzadeh… - Expert Systems with …, 2023 - Elsevier
Detecting brain tumors plays an important role in patients' lives as it can help specialists
save them or let them succumb to a terminal illness otherwise. Magnetic Resonance …

Federated fusion of magnified histopathological images for breast tumor classification in the internet of medical things

BLY Agbley, JP Li, AU Haq, EK Bankas… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Breast tumor detection and classification on the Internet of Medical Things (IoMT) can be
automated with the potential of Artificial Intelligence (AI). Deep learning models rely on large …

A comprehensive review of tubule formation in histopathology images: advancement in tubule and tumor detection techniques

JJW Siet, XJ Tan, WL Cheor, KS Ab Rahman… - Artificial Intelligence …, 2024 - Springer
Breast cancer, the earliest documented cancer in history, stands as a foremost cause of
mortality, accounting for 684,996 deaths globally in 2020 (15.5% of all female cancer cases) …

Deep learning-based methods for classification of microsatellite instability in endometrial cancer from HE-stained pathological images

Y Zhang, S Chen, Y Wang, J Li, K Xu, J Chen… - Journal of Cancer …, 2023 - Springer
Background Microsatellite instability (MSI) is one of the essential tumor biomarkers for
cancer treatment and prognosis. The presence of more significant PD-L1 expression on the …

DiagCovidPNA: diagnosing and differentiating COVID-19, viral and bacterial pneumonia from chest X-ray images using a hybrid specialized deep learning approach

V Mohammadian Takaloo, M Hashemzadeh… - Soft Computing, 2024 - Springer
In this study, the DiagCovidPNA method is proposed to aid in diagnosing and differentiating
COVID-19 disease and viral and bacterial pneumonia (PNA) from chest X-ray (CXR) …

SPS vision net: Measuring sensory processing sensitivity via an artificial neural network

N Sadeghzadeh, N Farajzadeh, N Dattatri… - Cognitive …, 2024 - Springer
Sensory processing sensitivity (SPS) is a biological trait associated with heightened
sensitivity and responsivity to the environment. One important question is how those with the …

IJES-OA Net: A residual neural network to classify knee osteoarthritis from radiographic images based on the edges of the intra-joint spaces

N Farajzadeh, N Sadeghzadeh… - Medical Engineering & …, 2023 - Elsevier
Among the musculoskeletal disorders in the world, osteoarthritis is the most common,
affecting most of the body joints, especially the knee. Clinical radiographic imaging methods …

NSSI questionnaires revisited: A data mining approach to shorten the NSSI questionnaires

N Farajzadeh, N Sadeghzadeh - Plos one, 2023 - journals.plos.org
Background and objective Non-suicidal self-injury (NSSI) is a psychological disorder that the
sufferer consciously damages their body tissues, often too severe that requires intensive …

Curvature generation based on weight-updated boosting using shoe last point-cloud measurements

D Wang, Z Li, N Dey, B Misra, RS Sherratt, F Shi - Heliyon, 2024 - cell.com
Lasts are foot-shaped forms made of plastic, wood, aluminum, or 3D-printed plastic. The last
of a shoe determines not only its shape and style but also how well it fits and protects the …

Integrating Transformer and Bidirectional Long Short-Term Memory for Intelligent Breast Cancer Detection from Histopathology Biopsy Images.

P Balaji, O Alqahtani, S Babu… - … in Engineering & …, 2024 - search.ebscohost.com
Breast cancer is a significant threat to the global population, affecting not only women but
also a threat to the entire population. With recent advancements in digital pathology, Eosin …