arXiv AI

Pediatric Bone Age Prediction Using Deep Learning

arXiv:2607. 16936v1 Announce Type: cross Abstract: Pediatric bone age prediction is a crucial task in clinical practice that can help diagnose endocrine disorders and provide insight into a child's growth and development.

arXiv AI

Jul 28

BoneAgeTW2: Automated Skeletal Maturation Assessment via the Tanner-Whitehouse 2 Method, Deep Learning, and Clinical Report Generation with Distribution Curves

arXiv:2607. 23224v1 Announce Type: cross Abstract: We present BoneAgeTW2, the first fully open-source system to automate the complete Tanner-Whitehouse 2 (TW2) clinical protocol for skeletal maturity assessment end-to-end.

By Juan Manuel Castillo Pinto

arXiv Machine Learning

Jul 30

Classification of Disease from Lungs X-ray Images using VGG16, VGG19 and ResNet50 Models

arXiv:2607. 26580v1 Announce Type: cross Abstract: With the increase in the number of cases related to respiratory diseases, there is an urgent need to detect them early and diagnose them accurately.

By Nand Lal Yadav, Rajesh Kumar, Satyendra Singh, Sudhakar Singh

arXiv AI

Jun 4

AttnRegDeepLab: A Two-Stage Decoupled Framework for Interpretable Embryo Fragmentation Grading

arXiv:2511. 18454v3 Announce Type: replace-cross Abstract: Embryo fragmentation is a morphological indicator critical for evaluating developmental potential in In Vitro Fertilization (IVF).

By Ming-Jhe Lee, Chang-Hong Wu, Jung-Hua Wang, Ming-Jer Chen, Yu-Chiao Yi, Tsung-Hsien Lee

computer-vision

arXiv Machine Learning

1d ago

Deep learning-based computed tomography (CT) derived body composition classifier for colorectal cancer patients

arXiv:2608. 15712v1 Announce Type: cross Abstract: Background: Accurate body composition analysis using Computed Tomography (CT) scans is essential for assessing skeletal muscle area (SMA) and skeletal muscle density (SMD), key markers of nutritional status in cancer patients.

By Eve Harling (James Watt School of Engineering, College of Science & Engineering, University of Glasgow, Glasgow, UK), Chattarin Pumtako (Academic Unit of Surgery, School of Medicine, College of Medical Veterinary & Life Sciences, University of Glasgow, Glasgow, UK), Bernd Porr (James Watt School of Engineering, College of Science & Engineering, University of Glasgow, Glasgow, UK), Donald C McMillan (Academic Unit of Surgery, School of Medicine, College of Medical Veterinary & Life Sciences, University of Glasgow, Glasgow, UK), Ross D Dolan (Academic Unit of Surgery, School of Medicine, College of Medical Veterinary & Life Sciences, University of Glasgow, Glasgow, UK)

computer-vision

arXiv AI

Jul 16

Beyond Backbone Backpropagation: A Decoupled Strategy for Efficient Transfer Learning

arXiv:2607. 13043v1 Announce Type: cross Abstract: Deep learning models achieve state-of-the-art image classification but face deployment challenges due to computational costs and energy demands.

By Daniel Vila-Cruz, Laura Mor\'an-Fern\'andez, Ver\'onica Bol\'on-Canedo

llms computer-vision fine-tuning benchmarks

arXiv AI

Jun 19

Interpretable Sperm Morphology Classification via Attention-Guided Deep Learning

arXiv:2606. 20438v1 Announce Type: new Abstract: Male infertility is a major cause of couple infertility, often linked to abnormal sperm morphology.

By Zahra Asghari Varzaneh, Reza Khoshkangini, Thomas Ebner, Lars Johansson

safety

arXiv AI

Jun 29

Automated brain tumor detection in MRI images using CNN and ResNet architectures

arXiv:2606. 27405v1 Announce Type: cross Abstract: Deep learning has shown significant potential in medical image analysis, particularly for disease detection using MRI scans.

By Annapurna V K, Asha N, K Paramesha, Shabana Sultana, Kirankumar Humse

fine-tuning

arXiv Machine Learning

Jun 25

Blasto-Net: An Explainable Multi-Task Learning for Blastocyst Segmentation, Grading, and Implantation Prediction

arXiv:2606. 25463v1 Announce Type: cross Abstract: This study introduces Blasto-Net, a multi-task deep learning model for comprehensive blastocyst analysis.

By Zahra Asghari Varzaneh, Reza Khoshkangini, Magnus Johnsson, Thomas Ebner, Lars Johansson

computer-vision

arXiv AI

2d ago

CMCNet: Aligning Ultrasound Image Embeddings with Textual TI-RADS Representations for Fine-Grained Thyroid Classification

arXiv:2608. 13939v1 Announce Type: cross Abstract: Ultrasound is the primary imaging modality for assessing thyroid nodules, and the ACR TI-RADS framework standardizes diagnosis through five ultrasound feature categories that are aggregated into five risk levels (TR1-TR5).

By Bingxin Yu, Xueli Wang, Jerry Zhou, Wenyan Wang, Li Wen, Lan Huang, Xin Feng, Fengfeng Zhou, Kewei Li

rag multimodal safety

arXiv AI

Jun 15

CottonLeafVision: An Explainable and Robust Deep Learning Framework for Cotton Leaf Disease Classification

arXiv:2606. 14686v1 Announce Type: cross Abstract: Globally, cotton is a highly economically beneficial crop, as the textile industry heavily depends on it.

By Rafi Ahamed, Md. Abir Rahman, Tasnia Tarannum Roza, Munaia Jannat Easha, Md. Asif Khan, Sudeepta Mandal

safety

arXiv AI

Jul 2

Enhancing Oracle Bone Inscription Recognition via Multi-Scale Layer Attention

arXiv:2607. 00057v1 Announce Type: cross Abstract: Oracle Bone Inscriptions (OBIs) recognition plays a crucial role in understanding ancient Chinese culture.

By Chaowen Yan, Kaishen Wang, Yong Wang, Jianlong Xiong, Tao He

computer-vision

arXiv AI

Aug 12

Energy and Performance Benchmarking of Deep Learning Models for Breast Cancer Detection

arXiv:2608. 09996v1 Announce Type: cross Abstract: Recent advances in machine learning have greatly improved breast cancer detection, enabling more accurate and timely diagnosis.

By Samar Garrab, Ghada Achour

llms benchmarks

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