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Jan 16, 2026Open    Access

Quantum-Inspired Feature Representations for Depression Subtype Classification: A Synthetic Benchmark Study

Rocco de Filippis,Abdullah Al Foysal
Depression is a clinically heterogeneous disorder comprising subtypes such as melancholic, atypical, anxious, and unspecified, each characterized by distinct symptom profiles and treatment responses. Accurate identification of these subtypes is essential for precision psychiatry and optimizing therapeutic outcomes. This study investigates the potential of quantum-inspired feature representations to enhance the classification of depression subtypes from clinical data. A synthetic dataset of 5000 ...
Open Access Library J.   Vol.13, 2026
Doi:10.4236/oalib.1114448


Jan 16, 2026Open    Access

AI-Enhanced Gut Brain Axis Profiling for Major Depressive Disorder: Integrating Synthetic Multi-Omics, Deep Learning, and Interpretable Precision Therapeutics

Rocco de Filippis,Abdullah Al Foysal
Major depressive disorder (MDD) has been repeatedly linked to disruptions of the gut brain axis (GBA), yet practical decision systems that convert multi-omics patterns into patient-specific guidance remain limited. We present an end-to-end, explainable pipeline that learns putative GBA signatures of MDD from synthetic data and translates model attributions into hypothesis-driven nutritional and pharmacological suggestions. We simulated a cohort of N = 1,500 individuals (30% MDD) comprising 200 m...
Open Access Library J.   Vol.13, 2026
Doi:10.4236/oalib.1114444


Jan 15, 2026Open    Access

Enhanced Multimodal Transformer for Treatment-Resistant Depression Prediction Using Synthetic fMRI, Genomic, and Clinical Data

Rocco de Filippis,Abdullah Al Foysal
Treatment-Resistant Depression (TRD) remains one of the most challenging subtypes of major depressive disorder, affecting approximately one-third of patients and leading to significant morbidity, healthcare costs, and reduced quality of life. Predicting TRD onset and progression is complex, as it requires integrating heterogeneous biomarkers spanning neuroimaging, genomics, and clinical history. This study presents an Enhanced Multimodal Transformer (EMT) designed to fuse functional magnetic res...
Open Access Library J.   Vol.13, 2026
Doi:10.4236/oalib.1114447


Jan 15, 2026Open    Access

Deep Learning for Predicting Post-Stroke Cognitive Decline Using Multimodal Data: A Synthetic Proof-of-Concept Study

Rocco de Filippis,Abdullah Al Foysal
Cognitive impairment is a frequent and debilitating outcome of stroke, profoundly affecting patient independence, recovery trajectories, and long-term quality of life. Despite its prevalence, accurate early prediction of post-stroke cognitive decline (PSCD) remains an unmet challenge due to the multifactorial interplay between structural brain lesions, neurophysiological changes, and diverse clinical comorbidities. In this study, we present a multimodal deep learning framework designed to classi...
Open Access Library J.   Vol.13, 2026
Doi:10.4236/oalib.1114446


Jan 15, 2026Open    Access

AI-Based Early Detection of Alzheimer’s Disease through Speech and Language Biomarkers: A Synthetic Proof-of-Concept Study

Rocco de Filippis,Abdullah Al Foysal
Early detection of Alzheimer’s disease (AD) is a critical yet unresolved challenge in neurology, as subtle cognitive and linguistic impairments often emerge years before formal diagnosis. Traditional approaches, including neuroimaging and cognitive testing, are limited by cost, invasiveness, and low sensitivity at prodromal stages. Speech and language markers have recently emerged as promising, non-invasive digital biomarkers that can be continuously monitored in naturalistic settings. In this s...
Open Access Library J.   Vol.13, 2026
Doi:10.4236/oalib.1114443


Jan 14, 2026Open    Access

Cross-Population Transfer Learning for Antidepressant Treatment Response Prediction: A SHAP-Based Explainability Approach Using Synthetic Multi-Ethnic Data

Rocco de Filippis,Abdullah Al Foysal
Accurate prediction of antidepressant treatment response remains a major challenge in psychiatry, particularly across diverse patient populations where genetic, demographic, and clinical characteristics vary substantially. In this study, we evaluate the potential of transfer learning to enhance predictive performance across heterogeneous cohorts. We generated a synthetic, population-stratified dataset representing four major demographic groups, European, East Asian, African, and Latin American, ...
Open Access Library J.   Vol.13, 2026
Doi:10.4236/oalib.1114445


Dec 23, 2025Open    Access

Reinforcement Learning for Antidepressant Dose Adjustment: An Explainable Agent Approach

Rocco de Filippis,Abdullah Al Foysal
Major Depressive Disorder (MDD) is a prevalent psychiatric condition requiring long-term pharmacological management, with escitalopram often prescribed as a first-line treatment. However, optimizing antidepressant dosing remains challenging due to heterogeneous patient responses, complex symptom trajectories, and variable tolerance to side effects. This study presents a Reinforcement Learning (RL) framework for dynamic dose adjustment, trained within a simulated patient environment designed to c...
Open Access Library J.   Vol.12, 2025
Doi:10.4236/oalib.1114449


Nov 26, 2025Open    Access

Case Report: Long-Term Survival in a Child with Alobar Holoprosencephaly—Developmental Improvement with Supportive Pharmacotherapy

Rasha Ibrahim Gabr
Holoprosencephaly (HPE) is a severe congenital brain malformation characterized by incomplete division of the prosencephalon, with the alobar form being the most severe and usually incompatible with long-term survival. Most affected infants die in utero or in the early neonatal period, and those who survive typically show profound neurodevelopmental impairment with minimal progress. Here, we report the case of a male child with MRI-confirmed alobar HPE who presented with seizures, gastroesophage...
Open Access Library J.   Vol.12, 2025
Doi:10.4236/oalib.1114504


Oct 24, 2025Open    Access

Severe and Rare Cerebrovascular Involvement in Systemic Lupus Erythematosus: Case Report and Literature Review

Abderrazzak Ajertil,Rim Jirari,Louis-Jaurès Kemel M’Benga,Abdeljalil El Quessar
Cerebral vasculitis is an uncommon but severe manifestation of systemic lupus erythematosus (SLE), often associated with complex management and unfavorable outcomes due to its neurological impact. We describe the case of a 32-year-old male with SLE who developed recurrent seizures and progressive cognitive decline. Clinical evaluation, laboratory investigations, and neuroimaging supported the diagnosis of lupus-related cerebral vasculitis. Despite aggressive immunosuppressive therapy, the patien...
Open Access Library J.   Vol.12, 2025
Doi:10.4236/oalib.1114321


Sep 28, 2025Open    Access

Autoimmune Myasthenia Gravis: Diagnosis and Management in a Young Patient Seen for Consultation at the National Reference General Hospital of N’Djamena (Chad)

Adoum Hamad Zenal Abidine,Boubacar Soumaila,Madjirabé Christian,Mht Alkher Ousmane,Guelngar Othon Carlos,Alhadj Mht Moustapha,Adoum Hamat Kaltam,Adoum Hamat Alfaris,Tahir Aiba,Abdel-Madjid Zakaria Zakaria,Toure Kamadore
Introduction: Myasthenia gravis is a neuromuscular junction disorder characterized by fatigability, muscle weakness affecting the oculomotor, bulbar, and skeletal muscles, worsening with exertion and resolving at rest. It is an autoimmune neurological disease that can be life-threatening due to respiratory muscle damage. Clinical Case: This is a 20-year-old male XL patient with no particular history who presents with muscle fatigue during exercise associated wit...
Open Access Library J.   Vol.12, 2025
Doi:10.4236/oalib.1113994


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