Graph theory analysis reveals functional brain network alterations in HIV-associated asymptomatic neurocognitive impairment in virally suppressed homosexual males by Xire Aili, Shuai Han, Juming Ma, Jiaojiao Liu, Wei Wang, Chuanke Hou, Xingyuan Jiang, Haixia Luo, Fan Xu, Ruili Li, Hongjun Li

“…Abstract Background This study aimed to investigate the global and nodal functional network alterations, abnormal connections of brain regions, and potential imaging biomarkers in virally suppressed people living with HIV (PLH) with asymptomatic neurocognitive impairment (ANI) using graph theory analysis. …”
Get full text

Multi-Layer Modeling and Visualization of Functional Network Connectivity Shows High Performance for the Classification of Schizophrenia and Cognitive Performance via Resting fMRI by Duc My Vo, Anees Abrol, Zening Fu, Vince D. Calhoun

“…<b>Background:</b> In functional magnetic resonance imaging (fMRI), functional network connectivity (FNC) captures temporal coupling among intrinsic connectivity networks (ICNs). …”
Get full text

Clinical efficacy and complications of 10 surgical interventions for cervical ossification of the posterior longitudinal ligament: an updated systematic review and network meta-ana... by Xiao Chen, Yuanhe Fan, Jie Chen, Hongliang Tu

“…Our search identified both randomized and non-randomized controlled trials compar ing the following surgical interventions: ACDF, ADF, ACCF, ACAF, PDIF, PDF, LC, LP, LF, and VBSO. The extracted data were subjected to network meta-analysis. Our analysis included the following outcome measures: Patient demographic characteristics, Japanese Orthopaedic Association (JOA) scores, JOA improvement rates, overall complication rates, excellent/good recovery rates, cervical lordosis characteristics, Visual Analog Scale (VAS) scores, Neck Disability Index (NDI) scores, surgical duration and intraoperative blood loss. …”
Get full text

Enhancing neurological disease diagnostics: fusion of deep transfer learning with optimization algorithm for acute brain stroke prediction using facial images by Fadwa Alrowais, Mohammed Alqahtani, Jahangir Khan, Achraf Ben Miled, Da’ad Albalawneh, Abdulwhab Alkharashi, Samah Al Zanin, Radwa Marzouk

“…The proposed ENDDFTL-ABSPFI method aims to enhance brain stroke detection and classification models using facial imaging. Initially, the image pre-processing stage applies the fuzzy-based median filter (FMF) model to eliminate the noise in input image data. …”
Get full text

The alteration of the sensorimotor network in trigeminal neuralgia after microvascular decompression surgery: a follow-up study using independent component analysis by Yan Zhang, Yan Zhang, Xueju Wang, Xuefeng Wang, Gengdi Huang

“…Resting-state functional magnetic resonance imaging (rs-fMRI) has been extensively applied in studies of TN, uncovering alterations in brain activity, functional connectivity, cortical thickness and neural networks.MethodsIndependent component analysis (ICA) presents a powerful alternative for analyzing fMRI data, offering several advantages over traditional region of interests (ROIs) approaches. …”
Get full text

Expedited Colorectal Cancer Detection Through a Dexterous Hybrid CADx System With Enhanced Image Processing and Augmented Polyp Visualization by Akella Subrahmanya Narasimha Raju, K. Venkatesh, Ranjith Kumar Gatla, Marwa M. Eid, Aymen Flah, Zdenek Slanina, Ramy N. R. Ghaly

“…The complexity and variability of medical imaging continue to impair the feasibility of early detection of colorectal cancer, despite its critical role in improving patient outcomes. …”
Get full text

Deep learning-based video analysis for automatically detecting penetration and aspiration in videofluoroscopic swallowing study by Soyoung Kwak, Jeoung Kun Kim, Jun Sung Moon, Gun Woo Lee, Sungho Kim, Min Cheol Chang

Get full text

DETECTION OF NON-MELANOMA SKIN CANCER BY DEEP CONVOLUTIONAL NEURAL NETWORK AND STOCHASTIC GRADIENT DESCENT OPTIMIZATION ALGORITHM by Premananda Sahu, Srikanta Kumar Mohapatra, Prakash Kumar Sarang, Jayashree Mohanty, Pradeepta Kumar Sarangi

“…Furthermore, we used HAM 10000 as the data set for training and testing purposes, as well as the feature extraction technique Principal Component Analysis. …”
Get full text

A Novel 3D Convolutional Neural Network-Based Deep Learning Model for Spatiotemporal Feature Mapping for Video Analysis: Feasibility Study for Gastrointestinal Endoscopic Video Cla... by Mrinal Kanti Dhar, Mou Deb, Poonguzhali Elangovan, Keerthy Gopalakrishnan, Divyanshi Sood, Avneet Kaur, Charmy Parikh, Swetha Rapolu, Gianeshwaree Alias Rachna Panjwani, Rabiah Aslam Ansari, Naghmeh Asadimanesh, Shiva Sankari Karuppiah, Scott A. Helgeson, Venkata S. Akshintala, Shivaram P. Arunachalam

“…Despite advances in DL, most existing models in medical AI focus on static images, overlooking critical temporal cues present in video data. …”
Get full text

An explainable-by-design end-to-end AI framework based on prototypical part learning for lesion detection and classification in Digital Breast Tomosynthesis images by Andrea Berti, Camilla Scapicchio, Chiara Iacconi, Charlotte Marguerite Lucille Trombadori, Maria Evelina Fantacci, Alessandra Retico, Sara Colantonio

“…However, the large data volume of DBT poses a challenge for timely analysis. …”
Get full text

Northern European Countries in Modern Global Value Chains: Comparative Analysis by Alexander D. Vasilchenko

Get full text

Variation within and between digital pathology and light microscopy for the diagnosis of histopathology slides: blinded crossover comparison study by David RJ Snead, Ayesha S Azam, Jenny Thirlwall, Peter Kimani, Louise Hiller, Adam Bickers, Clinton Boyd, David Boyle, David Clark, Ian Ellis, Kishore Gopalakrishnan, Mohammad Ilyas, Paul Kelly, Maurice Loughrey, Desley Neil, Emad Rakha, Ian SD Roberts, Shatrughan Sah, Maria Soares, YeeWah Tsang, Manuel Salto-Tellez, Helen Higgins, Donna Howe, Abigail Takyi, Yan Chen, Agnieszka Ignatowicz, Jason Madan, Henry Nwankwo, George Partridge, Janet Dunn

“…The advantages DP offers will not be realised if on implementation pathologists and/or technicians have to constantly move between systems to complete tasks or if networking speed impacts the systems performance. The need for accurate data on the benefits of DP is likely to be important in helping laboratories make the decision to transition to DP. …”
Get full text

Comparative efficacy and acceptability of interventions for universal, selective and indicated prevention of eating disorders: study protocol for a systematic review and network me... by Sandra Schlegl, Felicitas Hirler, Andreas Gerich, Mikkel Højlund, Eric Stice, Tracey Wade, Denise Wilfley, James Downs, Ulrich Voderholzer, Jasmine Perry, Verena Haas, Marco Solmi, Christoph Correll

“…This article outlines a systematic review and network meta-analysis (NMA) protocol to assess the comparative effectiveness of various ED preventive interventions across different prevention types and populations. …”
Get full text

Img2Neuro: brain-trained neural activity encoders for enhanced object recognition by Mona A Aboelnaga, Mohamed W El-Kharashi, Seif Eldawlatly

“…This is manifested in the significant superiority of the brain in comparison to the developed models in terms of the accuracy and the amount of data needed for training. Therefore, rather than using the brain as an inspiration, in this paper, we introduce Img2Neuro; a convolutional neural network model feature extractor that predicts the visual brain’s response to images by encoding neural activity. …”
Get full text

DeSPPNet: A Multiscale Deep Learning Model for Cardiac Segmentation by Elizar Elizar, Rusdha Muharar, Mohd Asyraf Zulkifley

“…Objectives: The objective of this study is to develop a multiscale deep learning model to segment cardiac organs based on MRI imaging data. Good segmentation performance is difficult to achieve due to the complex nature of the cardiac structure, which includes a variety of chambers, arteries, and tissues. …”
Get full text

Protocol for performing and analyzing a live-cell imaging-based microglia phagocytosis assay using AI on the Olympus ScanR system by Alexander Zähringer, Janaki Manoja Vinnakota, Tobias Wertheimer, Marie Follo, Robert Zeiser

“…We then explain the workflow of live-cell imaging and usage of AI in the data analysis. This protocol facilitates the preparation of phagocytosis assays and improves accuracy in data analysis.For complete details on the use and execution of this protocol, please refer to Zähringer et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.…”
Get full text

DDD++: Exploiting Density map consistency for Deep Depth estimation in indoor environments by Giovanni Pintore, Marco Agus, Alberto Signoroni, Enrico Gobbetti

Get full text

Comparative Evaluation of Multimodal Large Language Models for No-Reference Image Quality Assessment with Authentic Distortions: A Study of OpenAI and Claude.AI Models by Domonkos Varga

Get full text

Deep learning models based on multiparametric magnetic resonance imaging and clinical parameters for identifying synchronous liver metastases from rectal cancer by Jing Sun, Pu-Yeh Wu, Fangmin Shen, Xingfa Chen, Jieqiong She, Mingcong Luo, Feifei Feng, Dechun Zheng

“…Abstract Objectives To establish and validate deep learning (DL) models based on pre-treatment multiparametric magnetic resonance imaging (MRI) images of primary rectal cancer and basic clinical data for the prediction of synchronous liver metastases (SLM) in patients with Rectal cancer (RC). …”
Get full text

Social Media Based Topic Modeling for Smart Campus: A Deep Topical Correlation Analysis Method by Jun Peng, Yiyi Zhou, Xiaoshuai Sun, Jinsong Su, Rongrong Ji

“…However, it is challenging to deal with multi-modal data (i.e., text, images, and videos contained in the social media data) as well as the modality dependence and missing modality. …”
Get full text