Author

Mohammad Alhefdi

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Open access Aug 2026

A Novel Channel-Spatial Deep Residual Attention Network for the Classification of Neurodegenerative Diseases from MRI Scans

Personalized and precise classification of neurodegenerative diseases (Alzheimer’s and brain tumors) is crucial for early diagnosis and patient care. Brain tumors and Alzheimer’s disease are challenging to classify due to their varied shapes and features. In this work, we propose a novel four-block residual attention m...

Wardah Ibrar, Muhammad Attique Khan, Syeda Anum Fatima Naqvi et al. · Cognitive Computation · 0 citations

#federated learning Open access Aug 2026

AI‐Enabled 6G Space‐Air‐Ground–Integrated Networks for Ultra‐Reliable Low Latency Internet of Medical Things Healthcare

An AI‐assisted resource scheduling and cooperative learning model in a space–air–ground combined network (SAGIN) to possess ultra‐reliable low‐latency Internet of Medical Things applications and a multi agent—deep deterministic policy gradient (MA‐DDPG) agent that allocates resources in a distributed manner and a hiera...

T. Sardar, Gousia Thahniyath, Ahlam I. Almusharraf et al. · Transactions on Emerging Tel... · 0 citations

Open access Jul 2026

A unified machine learning framework for intelligent resource allocation toward 6G wireless communications.

A Dual-Stage Multi-Time-Scale Temporal Attention-Based LSTM network (D-MTSTA-LSTM) has been architected, which effectively learns short- and long-term relationships in network trends, thereby precisely predicting optimal communication routes and associated power and spectrum allocation.

Nishu Gupta, Rupali Bhartiya, S. Rathod et al. · Scientific Reports · 0 citations