AIMC Topic: Deep Learning

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Web based AI-driven framework combining multi-modal data with CNN and LLM for Parkinson's disease diagnosis.

Scientific reports
Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by a wide spectrum of motor and non-motor symptoms, often leading to delayed or inaccurate diagnosis. Conventional diagnostic methods frequently suffer from limited se...

Leveraging fundus images for on device eye disease diagnosis with AI powered lightweight software hardware framework.

Scientific reports
Vision loss due to illness can result from various medical conditions that affect the eyes. Advanced devices like OCT and ultra-widefield retinal cameras are expensive, making them less accessible in resource-limited settings. While eye image capture...

Artificial intelligence-based method for detecting wrist fractures in children.

Scientific reports
Pediatric wrist fractures are common skeletal injuries in clinical practice; however, due to the ongoing development of children's bones, fracture characteristics are complex and often prone to misdiagnosis or missed diagnosis. Moreover, traditional ...

Prognostic prediction in soft-tissue sarcomas using deep learning and digital pathology of tumor and margin areas.

Scientific reports
The histological FNCLCC grade is the primary prognostic factor in soft-tissue sarcoma (STS) but fails to fully capture high risk patients. This study aimed to develop and validate a deep learning (DL) model to predict metastatic relapse-free survival...

Deep learning-guided rational engineering of synergistic PD-1 and LAG-3 blockade for enhanced tumor immunomodulation.

Journal of computer-aided molecular design
Evolution has optimized proteins over time by the incorporation of precise and context-specific amino acid substitutions adapted to structural and functional demands. We have reconceptualized this principle using deep learning to engineer monoclonal ...

Design, synthesis, deep learning-guided prediction, and biological evaluation of novel pyridine-thiophene-based imine-benzalacetophenone hybrids as promising antimicrobial agent.

Journal of computer-aided molecular design
Antimicrobial resistance (AMR) remains a global health crisis, necessitating the development of novel therapeutics against multidrug-resistant pathogens. In this study, ten (10) hybrid imine-benzalacetophenone derivatives (7a-7j), incorporating pyrid...

Mycobacterium tuberculosis FAS-II pathway targeted integrative deep learning based identification of potential anti-tubercular agents.

Journal of computer-aided molecular design
Mycobacterium tuberculosis (Mtb) continues to be one of the major contributors to the global burden of infectious diseases. Many drugs used in the current treatment regime have fallen prey to the puzzling phenomenon of antimicrobial resistance. Despi...

Deep learning-based non-invasive differential diagnosis of eyelid basal cell and sebaceous gland carcinomas using photographic images.

International ophthalmology
PURPOSE: Pathological examination, the current gold standard for differentiating eyelid basal cell carcinoma (BCC) and sebaceous gland carcinoma (SGC), is invasive, time-consuming, and often inaccessible in primary care hospitals. Therefore, a non-in...

Application of deep learning in behavior recognition and early warning system for campus safety management.

PloS one
Campus safety is an essential concern as schools, colleges, and universities work to create secure environments for students, staff, and visitors. Many existing security systems are not fully effective at detecting unusual behaviors or sending fast a...

Attention to detail: A conditional multi-head transformer for traffic sign recognition.

PloS one
The challenge of traffic sign detection and recognition for driving vehicles has become more critical with recent advances in autonomous and assisted driving technologies. Although object recognition problems, particularly traffic sign recognition, h...