Article
Radiology, Nuclear Medicine & Medical Imaging
Erik Verburg, Carla H. van Gils, Bas H. M. van der Velden, Marije F. Bakker, Ruud M. Pijnappel, Wouter B. Veldhuis, Kenneth G. A. Gilhuijs
Summary: The study aimed to validate the integration of CAT and CAD in the second screening round, to reduce the workload of radiologists and the number of biopsies on benign lesions without missing cancer. The results showed that CAT correctly dismissed 950 examinations with 49 lesions in total, and subsequent CAD classified 132 lesions as benign without misclassifying any malignant lesion. The combined application of CAT and CAD significantly reduced false-positive lesions compared to radiological reading alone.
INVESTIGATIVE RADIOLOGY
(2023)
Article
Biotechnology & Applied Microbiology
Yifeng Dou, Wentao Meng
Summary: This paper introduces the research, prediction, and diagnosis methods of breast cancer, using the improved optimization algorithm GSP_SVM, which shows excellent performance in breast cancer diagnosis and improves the diagnostic efficiency of medical institutions.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2021)
Review
Radiology, Nuclear Medicine & Medical Imaging
Anna H. Koch, Lara S. Jeelof, Caroline L. P. Muntinga, T. A. Gootzen, Nienke M. A. van de Kruis, Joost Nederend, Tim Boers, Fons van der Sommen, Jurgen M. J. Piek
Summary: This study evaluated the feasibility of computer-aided diagnostics (CAD) in predicting the chance of malignancy of ovarian tumors. The results showed that CAD based on ultrasound, CT scans, and MRI scans has high performance and potential cost-effectiveness in assessing ovarian tumors. However, more large datasets and external validation are needed to make the results generalizable.
INSIGHTS INTO IMAGING
(2023)
Review
Oncology
Xin Yu Liew, Nazia Hameed, Jeremie Clos
Summary: Early detection and timely treatment of breast cancer can reduce the risk of death, with histopathology images and CAD systems being key technologies. Machine learning methods are increasingly applied in diagnosing breast cancer, helping to improve accuracy.
Article
Computer Science, Software Engineering
Konstantin Dmitriev, Joseph Marino, Kevin Baker, Arie E. Kaufman
Summary: Machine learning is a powerful tool for medical image analysis, with CAD systems often analyzed in terms of accuracy. This study presents a visual analytics approach to uncover the decision-making process of a CAD system for classifying pancreatic cystic lesions, utilizing both RF and CNN algorithms, eye tracking, and case-based visual aids.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2021)
Article
Oncology
Jing-Hang Ma, Shang-Feng You, Ji-Sen Xue, Xiao-Lin Li, Yi-Yao Chen, Yan Hu, Zhen Feng
Summary: Computer-aided diagnosis system plays an important role in cervical lesion diagnosis by using auto-segmented colposcopic images to extract features, augmenting minority data, and generating preliminary diagnosis results. The system improves sensitivity while maintaining acceptable specificity and accuracy.
FRONTIERS IN ONCOLOGY
(2022)
Article
Biology
Yassir Edrees Almalki, Muhammad Umair Ali, Waqas Ahmed, Karam Dad Kallu, Amad Zafar, Sharifa Khalid Alduraibi, Muhammad Irfan, Mohammad Abd Alkhalik Basha, Hassan A. Alshamrani, Alaa Khalid Alduraibi
Summary: Brain tumors reduce life expectancy and their timely diagnosis is crucial for saving lives. This study proposes a machine learning approach using MRI to accurately diagnose the severity of brain tumors and achieves promising results on an online brain MRI image dataset.
Review
Engineering, Biomedical
Haizhe Jin, Cheng Yu, Zibo Gong, Renjie Zheng, Yinan Zhao, Quanwei Fu
Summary: This study systematically analyzed and compared the performance of machine learning algorithms using the same dataset in the diagnosis of pulmonary nodules through a literature review.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Review
Health Care Sciences & Services
Scarlet Nazarian, Ben Glover, Hutan Ashrafian, Ara Darzi, Julian Teare
Summary: Artificial intelligence technologies show great potential in improving the detection and characterization of colorectal polyps, ultimately reducing the incidence of colorectal cancer. The current generation of AI-based systems demonstrate impressive accuracy in detecting and characterizing colorectal polyps.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2021)
Article
Chemistry, Analytical
Nitsa J. Herzog, George D. Magoulas
Summary: Early identification of degenerative processes in the human brain, especially structural and functional changes, is crucial for proper care and monitoring of related diseases. This study proposes a data processing pipeline on commodity hardware that utilizes brain asymmetry features for machine learning classification, showing promising results in distinguishing between normal cognition and early or progressive dementia patients.
Article
Computer Science, Interdisciplinary Applications
Jakub Ceranka, Joris Wuts, Ophelye Chiabai, Frederic Lecouvet, Jef Vandemeulebroucke
Summary: A fully automated computer-aided diagnosis system for the detection and segmentation of metastatic bone disease using whole-body multi-parametric MRI is proposed. The system outperformed state-of-the-art methodologies, achieving a detection sensitivity of 63% with an average of 6.44 false positives per image, and an average lesion Dice coefficient of 0.53.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2023)
Article
Computer Science, Artificial Intelligence
Mai S. Mabrouk, Heba M. Afify, Samir Y. Marzouk
Summary: This study investigates the use of CAD system for 3D image reconstruction of MR brain and tumor structures, incorporating FCM algorithm for image segmentation and SVM for tumor detection. The results show that this 3D model supports an advanced view of human brain diseases.
INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION
(2021)
Article
Cell Biology
Si-Yuan Lu, Suresh Chandra Satapathy, Shui-Hua Wang, Yu-Dong Zhang
Summary: Brain tumors are a major cause of human mortality, with over 120 different types falling into primary and metastatic categories. Early detection of primary brain tumors is crucial, and this study presented a novel computer-aided diagnosis system, PBTNet, for accurately identifying primary brain tumors in MRI images. By utilizing a pre-trained ResNet-18 as the backbone model and three randomized neural networks as classifiers, the PBTNet demonstrated effectiveness in classification performance through 5-fold cross-validation.
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
(2021)
Article
Multidisciplinary Sciences
Jessie Liu, Blanca Gallego, Sebastiano Barbieri
Summary: This paper proposes a learning to defer with uncertainty algorithm for computer-aided diagnosis, which identifies patients with high diagnostic uncertainty and defers them for evaluation by human experts. The algorithm is evaluated on different diagnosis tasks and compared with other methods, showing a good balance between diagnostic accuracy and deferral rate.
SCIENTIFIC REPORTS
(2022)
Article
Multidisciplinary Sciences
Zhongzhi Yu, Yemin Shi
Summary: In computer-aided diagnosis (CAD), accurately defining the decision boundary between known and unknown classes is a challenging task. This paper proposes a Centralized Space Learning (CSL) method that learns a centralized space to separate known and unknown classes, improving the robustness of CAD.
SCIENTIFIC REPORTS
(2023)
Article
Clinical Neurology
Fei Ye, Jiaoxing Li, Tianzhu Wang, Kai Lan, Haiyan Li, Haoyuan Yin, Tongli Guo, Xiong Zhang, Tingting Yang, Jie Liang, Xiaoxin Wu, Qi Li, Wenli Sheng
Summary: The study concluded that antiplatelet agents were effective and safe in preventing further cerebral ischemic attacks in adult patients with ischemic Moyamoya disease. Patients with a family history or previous stroke are at higher risk for recurrent strokes.
FRONTIERS IN NEUROLOGY
(2021)
Article
Cardiac & Cardiovascular Systems
Wen-Song Yang, Shu-Qiang Zhang, Yi-Qing Shen, Xiao Wei, Li-Bo Zhao, Xiong-Fei Xie, Lan Deng, Xin-Hui Li, Xin-Ni Lv, Fa-Jin Lv, Dar Dowlatshahi, Qi Li, Peng Xie
Summary: The study revealed that NCCT markers are independently associated with IVH growth and RHE, with the expansion-prone hematoma showing higher predictive accuracy. These findings can aid in risk stratification based on NCCT markers for predicting active bleeding.
JOURNAL OF THE AMERICAN HEART ASSOCIATION
(2021)
Review
Medicine, General & Internal
Peter B. Sporns, Marios-Nikos Psychogios, Gregoire Boulouis, Andreas Charidimou, Qi Li, Enrico Fainardi, Dar Dowlatshahi, Joshua N. Goldstein, Andrea Morotti
Summary: Intracerebral hemorrhage (ICH) accounts for 10% to 20% of all strokes worldwide and is associated with high morbidity and mortality. Neuroimaging plays a crucial role in the rapid diagnosis of ICH, identification of ICH expansion, and assessment of early hematoma expansion risk.
JOURNAL OF CLINICAL MEDICINE
(2021)
Article
Biophysics
Yineng Zheng, Xingming Guo, Yingying Wang, Jian Qin, Fajin Lv
Summary: A machine learning model utilizing multi-scale and multi-domain heart sound features was proposed for ACC/AHA HF stage classification. The LS-SVM demonstrated better classification performance compared to other classifiers, achieving high sensitivity, specificity, and accuracy on the testing set.
PHYSIOLOGICAL MEASUREMENT
(2022)
Article
Neurosciences
Zi-Jie Wang, Rui Zhao, Xiao Hu, Wen-Song Yang, Lan Deng, Xin-Ni Lv, Zuo-Qiao Li, Jing Cheng, Ming-Jun Pu, Zhou-Ping Tang, Guo-Feng Wu, Li-Bo Zhao, Peng Xie, Qi Li
Summary: The global SVD score is associated with small ICH and is inversely correlated with hematoma volume, especially in non-lobar ICH.
FRONTIERS IN NEUROSCIENCE
(2022)
Article
Clinical Neurology
Xiao Hu, Mingjun Pu, Zijie Wang, Jialun Yu, Xiaofang Wu, Jing Cheng, Chu Chen, Hao Yin, Tiannan Yang, Zhehao Zhang, Libo Zhao, Peng Xie, Qi Li
Summary: Objective dysphagia is a common complication of acute ischemic stroke, and predicting dysphagia is important for post-stroke treatment. This study aimed to identify predictors of dysphagia and swallowing function recovery after stroke and to investigate the location of dysphagia-associated lesions. The findings showed that initial risk of aspiration, aphasia, and larger white matter hyperintensity were significant predictors of swallowing function recovery. The right corona radiata was identified as an important brain area for dysphagia.
NEUROLOGICAL SCIENCES
(2023)
Article
Immunology
Sai Luo, Wen-Song Yang, Yi-Qing Shen, Ping Chen, Shu-Qiang Zhang, Zhen Jia, Qi Li, Jian-Ting Zhao, Peng Xie
Summary: This study aimed to investigate the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and D-dimer-to-fibrinogen ratio (DFR) as predictors of pneumonia and poor outcomes in patients with acute intracerebral hemorrhage (ICH). The results showed that NLR and PLR were independent predictors of pneumonia, while NLR and DFR were independent predictors of poor 90-day outcomes.
FRONTIERS IN IMMUNOLOGY
(2022)
Article
Oncology
Qianqian Si, Yuming Teng, Caiyan Liu, Weizhuang Yuan, Xiaoyuan Fan, Xiaoqian Zhang, Zongmuyu Zhang, Mingli Li, Qing Liu, Peng Wang, Zhongrui Yan, Bo Wu, Qiang Liu, Hangjuan Li, Yan Ji, Yuncai Ran, Bo Song, Shiguang Zhu, Hongyan Li, Jingxia Guan, Manli Zhao, Yonggang Hao, Pengfei Wang, Hong Bian, Ningfen Wang, Yulin Wang, Yuning Pan, Hongwei An, Rong Guo, Cong Han, Junshi Zhang, Hebo Wang, Yong You, Hongquan Jiang, Zifan Liu, Jingli Liu, Dingbo Tao, Xiangyu Piao, Jiangtao Zhang, Pei Wang, Shen Yang, Zhou Liu, Xiue Wei, Kai Han, Zhimin Shi, Aihua Liu, Zuowen Zhang, Chunye Ma, Baichen Wang, Gejuan Zhang, Chengguang Song, Guilian Zhang, Xiao Yang, Bing Chen, Baoquan Lu, Beilei Chen, Meng Zuo, Kun Han, Xiaodan Zhang, Wenfeng Cao, Lingfeng Wu, Qi Li, Xiaokun Geng, Junshan Zhou, Mengfei Zhong, Minghua Wang, Yangmei Chen, Jiachun Liu, Tingrui Wang, Youqing Deng, Weihai Xu
Summary: The SICO-ICAS study aims to elucidate the pathophysiology of stroke and cognitive impairment in the ICAS population, comprehensively evaluating the complex interactions among life-course exposure, genomic variation, vascular risk factors, cerebrovascular burden, and coexisting neurodegeneration.
ANNALS OF TRANSLATIONAL MEDICINE
(2022)
Article
Emergency Medicine
Andrew D. Warren, Qi Li, Kristin Schwab, Brenna McKaig, Alexa N. Goldstein, Steven M. Greenberg, Anand Viswanathan, Christopher Anderson, M. Edip Gurol, Aman Patel, Joshua N. Goldstein
Summary: Intraventricular hemorrhage (IVH) is common after intracerebral hemorrhage (ICH) and is associated with higher mortality and worse clinical outcome. The use of external ventricular drains (EVDs) is associated with lower mortality but not clearly with better neurologic outcome in ICH patients. Moreover, more rapid EVD placement is associated with higher mortality, potentially indicating early development of herniation or obstructive hydrocephalus.
INTERNATIONAL JOURNAL OF EMERGENCY MEDICINE
(2022)
Article
Biology
Yineng Zheng, Xingming Guo, Yang Yang, Hui Wang, Kangla Liao, Jian Qin
Summary: This study proposed a transfer learning-based model using phonocardiogram to detect left ventricular diastolic dyfunction noninvasively. Four different spectrogram representations of PCG signals were generated using STFT, MFCCs, S-transform and gammatonegram, and four pre-trained CNNs were employed to extract deep features. Feature subsets were selected using principal component analysis and linear discriminant analysis, and fused for classification using CatBoost. The proposed model achieved high performance in diastolic dysfunction detection.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Clinical Neurology
Qi Li, Andrea Morotti, Andrew Warren, Adnan Qureshi, Dar Dowlatshahi, Guido Falcone, Kevin N. Sheth, Ashkan Shoamanesh, Santosh B. Murthy, Anand Viswanathan, Joshua N. Goldstein
Summary: Objective: This study aimed to determine whether intensive blood pressure reduction could benefit patients with fast bleeding intracerebral hemorrhage (ICH). The results suggest that early use of intensive blood pressure reduction may reduce hematoma growth and improve outcomes in fast bleeding patients.
ANNALS OF NEUROLOGY
(2023)
Article
Neurosciences
Xiao Hu, Zhong-Song Xiao, Yi-Qing Shen, Wen-Song Yang, Peng Wang, Pei-Zheng Li, Zi-Jie Wang, Ming-Jun Pu, Li-Bo Zhao, Peng Xie, Qi Li
Summary: This study investigated the relationship between several inflammatory biomarkers and cerebral small vessel disease (CSVD) features. The results showed that the SERPINA3 level was associated with WMH severity, revealing a novel biomarker for CSVD and validating its relationship with inflammation and endothelial dysfunction.
CNS NEUROSCIENCE & THERAPEUTICS
(2023)
Article
Neurosciences
Zhongsong Xiao, Peizheng Li, Yiqing Shen, Anatol Manaenko, Wensong Yang, Peng Wang, Xinhui Li, Fangyu Liu, Peng Xie, Qi Li
Summary: Despite limited treatment options for intracerebral hemorrhage (ICH), recent evidence suggests that the ultra-early stage of ICH may have significant importance. This study investigated the metabolic changes induced by ICH in the ultra-early stage using a mouse model and identified key pathological mechanisms associated with this stage.
EXPERIMENTAL NEUROLOGY
(2023)
Article
Critical Care Medicine
Xiao-Fang Wu, Lan Deng, Xin-Ni Lv, Zuo-Qiao Li, Zi-Jie Wang, Xiao Hu, Ming-Jun Pu, Chu Chen, Li-Bo Zhao, Qi Li
Summary: This study investigated the clinical, imaging, and outcome characteristics of intracerebral hemorrhage (ICH) caused by structural vascular lesions. Compared to primary ICH, ICH caused by structural vascular lesions was found to occur in younger patients with a lower incidence of hypertension and diabetes. These patients predominantly had lobar hemorrhages and smaller baseline hematoma volumes. Additionally, they had lower mortality rates at 30 days and 3 months and better functional outcomes at 3 months.
NEUROCRITICAL CARE
(2023)
Review
Medicine, General & Internal
Xin-Ni Lv, Zuo-Qiao Li, Qi Li
Summary: Intracerebral hemorrhage is a dangerous subtype of stroke with high rates of morbidity and mortality. Targeting prevention of hematoma growth and perihematomal edema expansion shows promise as a therapeutic approach. Blood-based biomarkers are being studied as potential diagnostic, predictive, and prognostic markers due to their accessibility and acceptance in clinical practice. Validation studies are needed to determine the usefulness of these biomarkers in the future.
JOURNAL OF CLINICAL MEDICINE
(2023)