Results 141 to 150 of about 52,953 (291)

Tumor Synthesis Conditioned on Radiomics

2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
Due to privacy concerns, obtaining large datasets is challenging in medical image analysis, especially with 3D modalities like Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Existing generative models, developed to address this issue, often face limitations in output diversity and thus cannot accurately represent 3D medical images.
Jonghun Kim, Inye Na, Eun Sook Ko, Hyunjin Park   +3 more
openaire   +4 more sources

Pretreatment Prediction of Tumor Recurrence in Breast Cancer After Neoadjuvant Systemic Therapy Using Machine Learning With Clinical and CT Radiomics Features

The Kaohsiung Journal of Medical Sciences, EarlyView.
ABSTRACT This study aimed to develop machine learning models for predicting tumor recurrence in breast cancer before neoadjuvant systemic therapy (NST) by integrating clinical and radiomic features derived from pretreatment computed tomography (CT).
Huei‐Yi Tsai, Jo‐Ching Wang, Wei‐Shiuan Chung, Jui‐Sheng Hsu, Shu‐Yen Lin, Ming‐Feng Hou, Ming‐Chung Chou   +6 more
wiley   +1 more source

What is radiomics? [PDF]

Radiomics is an emerging field that combines medical imaging techniques with data science to extract a vast array of quantitative features from images for clinical or research applications.
Crombie, Katherine, Novak, Jan, Griffiths-King, Daniel, Mulvany, Timothy, Apps, John R.   +4 more
core   +1 more source

Efficacy of Negative Pressure Suction‐Assisted Flexible Ureteroscopy for Upper Urinary Tract Calculi and Construction of a Stone‐Free Rate Prediction Model

The Kaohsiung Journal of Medical Sciences, EarlyView.
ABSTRACT This study retrospectively analyzed 92 patients who underwent negative‐pressure suction sheath‐assisted flexible ureteroscopic lithotripsy (observation group) and 85 patients who underwent conventional flexible ureteroscopic lithotripsy (control group).
Ren‐Hui Qiu, Ding‐Sheng He, Chun‐Yu Guo, Li Dong, Guo‐Zhang Lin   +4 more
wiley   +1 more source

MRI‐based deep learning models match or surpass physician performance for early detection and staging of avascular necrosis of the femoral head: A systematic review

Knee Surgery, Sports Traumatology, Arthroscopy, EarlyView.
Abstract Purpose Efficient and reliable magnetic resonance imaging (MRI)‐based diagnosis of early avascular necrosis of the femoral head (AVNFH) is essential for guiding treatment but remains challenging due to variability in clinician experience. Deep learning (DL) models offer a promising solution. This review evaluates and summarizes the performance
Khaled Skaik, Jean Pierre Abdallah, Marc Daniel Bouchard, Olufemi R. Ayeni, Mahmoud Almasri   +4 more
wiley   +1 more source

Artificial intelligence across the continuum of care for the aging musculoskeletal patient: From longitudinal phenotyping to personalized surgery and recovery monitoring

Knee Surgery, Sports Traumatology, Arthroscopy, EarlyView.
Abstract Musculoskeletal care is being reshaped by population aging, multimorbidity, frailty, osteoporosis, sarcopenia, polypharmacy and increasing vulnerability to postoperative loss of independence. Artificial intelligence (AI) has entered orthopaedic research, but its clinical translation remains constrained. Many models address isolated diagnostic,
Felix C. Oettl, Balint Zsidai, James A. Pruneski, Jacob F. Oeding, Umile Giuseppe Longo, Michael T. Hirschmann, Ro Du Hyun, Kristian Samuelsson, ESSKA Artificial Intelligence Committee   +8 more
wiley   +1 more source

Machine Learning Radiomics for Predicting Response to MR-Guided Radiotherapy in Unresectable Hepatocellular Carcinoma: A Multicenter Cohort Study [PDF]

Ke Su,1– 3,* Xin Liu,1,4,* Yue-Can Zeng,5,* Junnv Xu,6,* Han Li,2 Heran Wang,7 Shanshan Du,1 Huadong Wang,1 Jinbo Yue,8 Yong Yin,1 Zhenjiang Li1 1Department of Radiation Physics, Shandong Cancer Hospital and Institute ...
Liu X, Yin Y, Zeng YC, Li H, Li Z, Du S, Su K, Wang H, Xu J, Yue J   +9 more
core  

Disease Duration Differentiates Freezing of Gait Response to Subthalamic and Nigral Stimulation for Parkinson's Disease in an Exploratory Multicenter Controlled Trial

Movement Disorders Clinical Practice, EarlyView.
Abstract Background Freezing of gait (FoG) belongs to most pressing unmet symptoms in the treatment of Parkinson's disease. Objectives To explore whether combined subthalamic and nigral (STN + SNr) deep brain stimulation improves FoG compared with optimized STN stimulation alone; to identify clinical variables associated with therapeutic response ...
Daniel Weiss, Idil Cebi, Marion Schütt, Imma Fischer, Lukas Pavelka, Pierre Kolber, Monika Pötter‐Nerger, Wolfgang Hamel, Andrea A. Kühn, Christian J. Hartmann, Kai Bötzel, Thomas Köglsperger, Michael T. Barbe, Zacharias Kohl, Steffen Paschen, Markus A. Hobert, Sergiu Groppa, Tobias Warnecke, Inga Claus, Rejko Krüger, Alireza Gharabaghi, For the Multicenter STN+SNr Study Group, Christian Stallinger, Frank Hertel, Daniel Kroneberg, Carsten Buhmann, Alessandro Gulberti, Beate Schönewald, Verena Zentsch, Verle Visser‐Vandewalle   +29 more
wiley   +1 more source

Mapping Tumor Recurrence and Metastasis With Pan‐Cancer Multi‐Omics

Med Research, EarlyView.
Tumor recurrence and metastasis arise from the interaction of shared evolutionary programs and context‐dependent modifiers. Clonal evolution, including genomic instability, subclonal selection, and treatment pressure, interacts with reversible cell‐state plasticity involving partial EMT, stemness, and dormancy, whereas immune escape, stromal remodeling,
Wenjun Meng, Ruicen Li, Xiaoli Mu, Xiaolong Tang, Yuxi Luo, Yingying Lei, Jinghong Xian, Guiyi Ji, Yihao Liu, Chenyu Huo, Sihan Li, Yalun Li, Jiadi Gan, Weimin Li   +13 more
wiley   +1 more source

Bibliometric Analysis of Research on Pituitary Adenomas: Recent Progress in Pathogenesis and Clinical Management

Medicine Advances, EarlyView.
A bibliometric analysis of 15,418 publications mapped global research on pituitary adenomas and identified 6 major research themes. Keyword trends highlighted the growing prominence of artificial intelligence‐related research. ABSTRACT Background Pituitary adenomas (PAs) comprise most of the tumors that originate from the sellar region.
Zhengyang Shen, Kan Deng, Lin Lu, Jifang Liu, Zhang Ye, Yi Zhang, Yong Yao   +6 more
wiley   +1 more source