AIMC Topic: Algorithms
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Paraphrase detection for Urdu language text using fine-tune BiLSTM framework.
Scientific reports
May 2, 2025
Automated paraphrase detection is crucial for natural language processing (NL) applications like text summarization, plagiarism detection, and question-answering systems. Detecting paraphrases in Urdu text remains challenging due to the language's co...
Comparison between logistic regression and machine learning algorithms on prediction of noise-induced hearing loss and investigation of SNP loci.
Scientific reports
May 2, 2025
To compare the comprehensive performance of conventional logistic regression (LR) and seven machine learning (ML) algorithms in Noise-Induced Hearing Loss (NIHL) prediction, and to investigate the single nucleotide polymorphism (SNP) loci significant...
Accuracy of an nnUNet Neural Network for the Automatic Segmentation of Intracranial Aneurysms, Their Parent Vessels, and Major Cerebral Arteries from MRI-TOF.
AJNR. American journal of neuroradiology
May 2, 2025
BACKGROUND AND PURPOSE: The automatic recognition of intracraial aneurysms by means of machine-learning algorithms represents a new frontier for diagnostic and therapeutic goals. Yet, the current algorithms focus solely on the aneurysms and not on th...
Deep Learning-Based Algorithm for Automatic Quantification of Nigrosome-1 and Parkinsonism Classification Using Susceptibility Map-Weighted MRI.
AJNR. American journal of neuroradiology
May 2, 2025
BACKGROUND AND PURPOSE: The diagnostic performance of deep learning model that simultaneously detecting and quantifying nigrosome-1 abnormality by using susceptibility map-weighted imaging (SMwI) remains unexplored. This study aimed to develop and va...
Development and Evaluation of Automated Artificial Intelligence-Based Brain Tumor Response Assessment in Patients with Glioblastoma.
AJNR. American journal of neuroradiology
May 2, 2025
This project aimed to develop and evaluate an automated, AI-based, volumetric brain tumor MRI response assessment algorithm on a large cohort of patients treated at a high-volume brain tumor center. We retrospectively analyzed data from 634 patients ...
Artificial intelligence for early detection of lung cancer in GPs' clinical notes: a retrospective observational cohort study.
The British journal of general practice : the journal of the Royal College of General Practitioners
May 2, 2025
BACKGROUND: The journey of >80% of patients diagnosed with lung cancer starts in general practice. About 75% of patients are diagnosed when it is at an advanced stage (3 or 4), leading to >80% mortality within 1 year at present. The long-term data in...
Navigating Through Whole Slide Images With Hierarchy, Multi-Object, and Multi-Scale Data.
IEEE transactions on medical imaging
May 2, 2025
Building deep learning models that can rapidly segment whole slide images (WSIs) using only a handful of training samples remains an open challenge in computational pathology. The difficulty lies in the histological images themselves: many morphologi...
Semi-Supervised Echocardiography Video Segmentation via Adaptive Spatio-Temporal Tensor Semantic Awareness and Memory Flow.
IEEE transactions on medical imaging
May 2, 2025
Accurate segmentation of cardiac structures in echocardiography videos is vital for diagnosing heart disease. However, challenges such as speckle noise, low spatial resolution, and incomplete video annotations hinder the accuracy and efficiency of se...
Model-Based Convolution Neural Network for 3D Near-Infrared Spectral Tomography.
IEEE transactions on medical imaging
May 2, 2025
Near-infrared spectral tomography (NIRST) is a non-invasive imaging technique that provides functional information about biological tissues. Due to diffuse light propagation in tissue and limited boundary measurements, NIRST image reconstruction pres...
Boosting Convolution With Efficient MLP-Permutation for Volumetric Medical Image Segmentation.
IEEE transactions on medical imaging
May 2, 2025
Recently, the advent of Vision Transformer (ViT) has brought substantial advancements in 3D benchmarks, particularly in 3D volumetric medical image segmentation (Vol-MedSeg). Concurrently, multi-layer perceptron (MLP) network has regained popularity ...
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