Automatic Characterization of Prostate Suspect Lesions on T2-Weighted Image Acquisitions Using Texture Features and Machine-Learning Methods: A Pilot Study by Teodora Telecan, Cosmin Caraiani, Bianca Boca, Roxana Sipos-Lascu, Laura Diosan, Zoltan Balint, Raluca Maria Hendea, Iulia Andras, Nicolae Crisan, Monica Lupsor-Platon

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Alterations of gray matter volume and functional connectivity in patients with cognitive impairment induced by occupational aluminum exposure: a case-control study by Huaxing Meng, Bo Liu, Xiaoting Lu, Yan Tan, Shanshan Wang, Baolong Pan, Hui Zhang, Qiao Niu

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Personal model‐assisted identification of NAD+ and glutathione metabolism as intervention target in NAFLD by Adil Mardinoglu, Elias Bjornson, Cheng Zhang, Martina Klevstig, Sanni Söderlund, Marcus Ståhlman, Martin Adiels, Antti Hakkarainen, Nina Lundbom, Murat Kilicarslan, Björn M Hallström, Jesper Lundbom, Bruno Vergès, Peter Hugh R Barrett, Gerald F Watts, Mireille J Serlie, Jens Nielsen, Mathias Uhlén, Ulf Smith, Hanns‐Ulrich Marschall, Marja‐Riitta Taskinen, Jan Boren

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Geometrical determinants of cerebral artery fenestration for cerebral infarction by Yuqian Mei, Xiaoqin Chen, Yao Zhang, Yanling Wang, Bo Wu, Mingcheng Hu, Quan Bao

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Toward a 10-W level femtosecond erbium laser operating in the 1600 nm low gain region by Haolin Yang, Ruili Zhang, Sailing He

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Current Status of CT Imaging Before Common Transcatheter Interventions for Structural Heart Disease by Rodrigo Salgado, Farah Cadour, Riccardo Cau, Luca Saba

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Integrating AI in college education: Positive yet mixed experiences with ChatGPT by Xinrui Song, Jiajin Zhang, Pingkun Yan, Juergen Hahn, Uwe Kruger, Hisham Mohamed, Ge Wang

“…With the launch of ChatGPT-4 Turbo in November 2023, we developed a ChatGPT-based teaching application (https://chat.openai.com/g/g-1imx1py4K-chatge-medical-imaging) and integrated it into our undergraduate medical imaging course in the Spring 2024 semester. …”
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Prognostic and Predictive Values of Metabolic Parameters of F-FDG PET/CT in Patients With Non-Small Cell Lung Cancer Treated With Chemotherapy by Xueyan Li MD, Dawei Wang BM, Lijuan Yu MD

“…Objectives: Increasing interests have been focused on using artificial intelligence (AI) to extend prognostic value of medical imaging. Feature extraction is a critical step for successful application of AI. …”
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Automatic Detection of Cracks in Cracked Tooth Based on Binary Classification Convolutional Neural Networks by Juncheng Guo, Yuyan Wu, Lizhi Chen, Guanghua Ge, Yadong Tang, Wenlong Wang

“…Current clinical diagnostic trials include traditional methods (such as occlusion test, probing, cold stimulation, etc.) and X-rays based medical imaging (periapical radiography (PR), cone-beam computed tomography (CBCT), etc.). …”
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Data-Efficient Bone Segmentation Using Feature Pyramid- Based SegFormer by Naohiro Masuda, Keiko Ono, Daisuke Tawara, Yusuke Matsuura, Kentaro Sakabe

“…These enhancements enable better image feature extraction and more precise object contour detection, which is particularly beneficial for medical imaging applications with limited training data.…”
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QuantumNet: An enhanced diabetic retinopathy detection model using classical deep learning-quantum transfer learning by Manish Bali, Ved Prakash Mishra, Anuradha Yenkikar, Diptee Chikmurge

“…QuantumNet demonstrates high accuracy and resource efficiency, providing a transformative solution for DR detection and broader medical imaging applications. The method is as follows: • Evaluate three classical deep learning models—CNN, ResNet50, and MobileNetV2—using the APTOS 2019 blindness detection dataset on Kaggle to identify the best-performing model for integration. • QuantumNet combines the best-performing classical DL model for feature extraction with a variational quantum classifier, leveraging quantum transfer learning for enhanced diagnostics, validated statistically and on Google Cirq using standard metrics. • QuantumNet achieves 94.11 % accuracy, surpassing classical DL models and prior research by 11.93 percentage points, demonstrating its potential for accurate, efficient DR detection and broader medical imaging applications.…”
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Blood Glucose Control Using a Novel Continuous Blood Glucose Monitor and Repetitive Intravenous Insulin Boluses: Exploiting Natural Insulin Pulsatility as a Principle for a Future... by Nils K. Skjaervold, Dan Östling, Dag R. Hjelme, Olav Spigset, Oddveig Lyng, Petter Aadahl

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Changes to Intermediary Metabolites in Sporadic and LRRK2 Parkinson’s Disease Demonstrated by Proton Magnetic Resonance Spectroscopy by Jan O. Aasly, Oddbjørn Sæther, Krisztina K. Johansen, Tone F. Bathen, Guro F. Giskeødegård, Linda R. White

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A Multimodal Convolutional Neural Network Based Approach for DICOM Files Classification. , 2025(1), e70107. by Mabirizi, Vicent, Wasswa, William, Kawuma, Simon

“…The study highlights its potential to improve medical imaging and support real-time clinical decision making. …”
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CASE PRESENTATION by Iuliana Iordan, Andreea Neculcea, Alina Mititelu, Claudiu Popescu, Ana Maria Vlădăreanu

“…Special evolution in myelofibrosis – case reports Neuroendocrine tumor (bronchial carcinoid) discovered after ocular symptoms – a case report Sepsis, dyspnea and cystic cardiac mass – the importance of medical imaging in the diagnostic algorithm Fistula complications of bevacizumab therapy in metastatic colorectal cancer – oncology surgeon’s point of view: a case presentation…”
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The Convergence of Nanotechnology, Biotechnology and Cancer Medicine in the Fourth Industrial Revolution by Steven Mufamadi, Zamanzima Mazibuko

“… Medical technologies of the fourth industrial revolution (Industry 4.0), such as nanotechnology, biotechnology, artificial  intelligence (AI), 3D printing and advanced materials are already transforming medical technology and the pharmaceutical industry by offering accurate diagnoses, targeting therapies with fewer side effects, and providing better medical imaging and personalised medicine. …”
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Application of a deep learning algorithm for the diagnosis of HCC by Philip Leung Ho Yu, Keith Wan-Hang Chiu, Jianliang Lu, Gilbert C.S. Lui, Jian Zhou, Ho-Ming Cheng, Xianhua Mao, Juan Wu, Xin-Ping Shen, King Ming Kwok, Wai Kuen Kan, Y.C. Ho, Hung Tat Chan, Peng Xiao, Lung-Yi Mak, Vivien W.M. Tsui, Cynthia Hui, Pui Mei Lam, Zijie Deng, Jiaqi Guo, Li Ni, Jinhua Huang, Sarah Yu, Chengzhi Peng, Wai Keung Li, Man-Fung Yuen, Wai-Kay Seto

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Breakthroughs in deep tumour penetrating nano‐phototheranostics for tumour ablation by Min‐Jun Baek, Sang Min Lee, Dae‐Duk Kim, Jae‐Young Lee

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Severity Assessment of COVID-19 Using a CT-Based Radiomics Model by Zhigao Xu, Lili Zhao, Guoqiang Yang, Ying Ren, Jinlong Wu, Yuwei Xia, Xuhong Yang, Milan Cao, Guojiang Zhang, Taisong Peng, Jiafeng Zhao, Hui Yang, Jinfeng Hu, Jiangfeng Du

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Magnetic Resonance Imaging of Mammalian Cells Individually Expressing Membrane-Associated Magnetosome Proteins I, L, B, and E by Qin Sun PhD, Gabriel Varela-Mattatall PhD, Prushoth Vivekanantha PhD, Moeiz Ahmed PhD, Salvan Hassan PhD, Selinia Hong PhD, Neil Gelman PhD, R. Terry Thompson PhD, Frank S. Prato PhD, Donna E. Goldhawk PhD

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