Multimodal Learning, Deep Learning, Financial Statement Analysis, LSTM, FinBERT, Financial Text Mining, Automated Interpretation, Financial Analytics Share and Cite: Wandwi, G. and Mbekomize, C. (2025 ...
Abstract: Batch normalization (BN) has proven to be a critical component in speeding up the training of deep spiking neural networks in deep learning. However, conventional BN implementations face ...
Introduction: Auditory brainstem response (ABR) is an objective neurophysiological evaluation designed to measure the electrical activity originating from the auditory nerve and brainstem in response ...
The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...
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MedicalPatchNet is a self-explainable deep learning architecture designed for chest X-ray classification that provides transparent and interpretable predictions without relying on post-hoc explanation ...
1 College of Mathematics and Computer Science, Chifeng University, Chifeng, China 2 General Surgery Thoracic Surgery, Chifeng Songshan Hospital, Chifeng, China Introduction: Breast cancer stands is a ...
Objective With a growing need for ultra-widefield fundus (UWF) fundus photographs in clinics and AI development, image quality assessment (IQA) of UWF fundus photographs is an important preceding step ...
Abstract: Brain tumor classification from MRI images plays a crucial role in early diagnosis and treatment planning. While deep learning approaches have shown promise in this domain, achieving high ...
Typically, an AI is "just" software. AI-powered software services like Grammarly and Rytr use neural nets, like GPT-3. Those neural nets consist of equations or commands, written in things like Python ...