Emerging Trends and Applications of Deep Learning for Biomedical Data Analysis

1. Deep learning, artificial intelligence, and bioinformatics promises innovations and imminent forecasts in SARS-COVID-19 genome data analysis<br>2. Integration of IoT and AI for potato leaf disease detection: enhancing agricultural efficiency and sustainability<br>3. A hybridized long–short-term memory networks-based deep learning model using reptile search optimization for COVID-19 prediction<br>4. Improving coronavirus classification accuracy with transfer learning and chest radiograph analysis<br>5. A hybrid deep neural network using the Levenberg–Marquardt algorithm applied to the nonlinear magnetohydrodynamic Jeffery–Hamel blood flow problem<br>6. An image segmentation method using intuitionistic fuzzy k-means and convolutional neural networks in multiclass image classification<br>7. Deep learning for wearable sensor data analysis<br>8. Unveiling emotions in real-time: a novel approach to face emotion recognition<br>9. Unleashing the power of convolutional neural networks for diabetic retinopathy detection in ophthalmology<br>10. Case studies and use cases of deep learning for biomedical applications<br>11. A convolutional neural network-based deep ensemble method for computed tomography scan image-based lung cancer diagnosis