AIMC Topic: Deep Learning

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ADC-MambaNet: a lightweight U-shaped architecture with mamba and multi-dimensional priority attention for medical image segmentation.

Biomedical physics & engineering express
Medical image segmentation is becoming a growing crucial step in assisting with disease detection and diagnosis. However, medical images often exhibit complex structures and textures, resulting in the need for highly complex methods. Particularly, wh...

AI-powered remote monitoring of brain responses to clear and incomprehensible speech via speckle pattern analysis.

Journal of biomedical optics
SIGNIFICANCE: Functional magnetic resonance imaging provides high spatial resolution but is limited by cost, infrastructure, and the constraints of an enclosed scanner. Portable methods such as functional near-infrared spectroscopy and electroencepha...

Artificial Intelligence for Head and Neck Squamous Cell Carcinoma: From Diagnosis to Treatment.

American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting
Head and neck squamous cell carcinoma (HNSCC) remains a globally prevalent malignancy with high morbidity and mortality. Despite therapeutic advances, patient outcomes are hindered by tumor heterogeneity, treatment-related toxicity, and the limitatio...

Enhancing corn industry sustainability through deep learning hybrid models for price volatility forecasting.

PloS one
The fluctuations in corn prices not only increase uncertainty in the market but also affect farmers' planting decisions and income stability, while also impeding crucial investments in sustainable agricultural practices. Collectively, these factors j...

BanglaNewsClassifier: A machine learning approach for news classification in Bangla Newspapers using hybrid stacking classifiers.

PloS one
Bangla news floods the web, and the need for smarter and more efficient classification techniques is greater than ever. Previous studies mostly focused on traditional models, overlooking the potential of hybrid techniques to handle the ever-growing c...

Data-Augmented Deep Learning Algorithm for Accurate Control of Bioethanol Fermentation Using an Online Raman Analyzer.

Biotechnology and bioengineering
Fed-batch fermentation has become the preferred strategy in many industrial biomanufacturing processes. However, a key challenge remains in optimizing the feeding strategy to achieve stable maximum yields. In this study, we present an online Raman sp...

Tailoring task arithmetic to address bias in models trained on multi-institutional datasets.

Journal of biomedical informatics
OBJECTIVE: Multi-institutional datasets are widely used for machine learning from clinical data, to increase dataset size and improve generalization. However, deep learning models in particular may learn to recognize the source of a data element, lea...

Performance of machine and deep learning models for predicting delirium in adult ICU patients: A systematic review.

International journal of medical informatics
PURPOSE: To summarize and evaluate the methodological quality of primary studies focusing on the use of machine or deep learning- based prediction models for delirium in ICU patients.

NeXtBrain: Combining local and global feature learning for brain tumor classification.

Brain research
The accurate and timely diagnosis of brain tumors is of paramount clinical significance for effective treatment planning and improved patient outcomes. While deep learning has advanced medical image analysis, concurrently achieving high classificatio...