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ISSN: 2950-1628

Research and application progress of radiomics in neurodegenerative diseases

Neurodegenerative diseases refer to degenerative diseases of the nervous system caused by neuronal degeneration and apoptosis. Usually, the onset of the disease is insidious, and the progression is...

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Ferroptosis, M6A and immune checkpoint-related gene expression in the middle temporal gyrus of the Alzheimer's disease brain

Alzheimer's disease (AD) is a common genetically related cognitive disorder. Studies have shown that ferroptosis, N⁶-Methyladenosine (M6A) and immune checkpoint are related to the development of AD....

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Metabolite changes and impact factors in mild traumatic brain injury patients: A review on magnetic resonance spectroscopy

The high incidence of mild traumatic brain injury (mTBI) and the associated post-concussion symptoms, such as headache and cognitive deficits, have captured the significant attention from researchers...

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A review of dose prediction methods for tumor radiation therapy

Radiation therapy (RT) is currently the main clinical treatment of tumors. Before treatment initiation, precise delineation of the planned target volume (PTV) and organs at risk (OAR) is essential....

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Review of large vision models and visual prompt engineering

Visual prompt engineering is a fundamental methodology in the field of visual and image artificial general intelligence. As the development of large vision models progresses, the importance of prompt...

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Radiological and clinical evaluation of triple combination modulating therapy effectiveness in adult patients with cystic fibrosis

Previous studies showed the clinical effectiveness of elexacaftor-tezacaftor-ivacaftor (ETI) in cystic fibrosis (CF) patients and a recently published study evaluated twelve CF patients that performed...

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Gray matter volume abnormalities in vascular cognitive impairment and their association with gene expression profiles

It has been revealed that brain gray matter volume (GMV) abnormalities are present in patients with vascular cognitive impairment (VCI). However, the GMV alterations that have been uncovered are highly...

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R2GenGPT: Radiology Report Generation with frozen LLMs

Large Language Models (LLMs) have consistently showcased remarkable generalization capa-bilities when applied to various language tasks. Nonetheless, harnessing the full potential of LLMs for Radiology...

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Dual-energy CT: A new frontier in oncology imaging

Malignant tumors have risen to prominence as the leading threat to both life and the overall health of individuals. Precision medicine relies heavily on precise imaging. Among the plethora of imaging...

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Artificial general intelligence for radiation oncology

The emergence of artificial general intelligence (AGI) is transforming radiation oncology. As prominent vanguards of AGI, large language models (LLMs) such as GPT-4 and PaLM 2 can process extensive...

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ChatGPT-based biological and psychological data imputation

Missing data are a common problem for large cohort or longitudinal research and have been handled through data imputation. Based on simplified models such as linear or nonlinear interpolations, current...

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A comprehensive survey of complex brain network representation

Recent years have shown great merits in utilizing neuroimaging data to understand brain structural and functional changes, as well as its relationship to different neurodegenerative diseases and other...

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Summary of ChatGPT-Related research and perspective towards the future of large language models

This paper presents a comprehensive survey of ChatGPT-related (GPT-3.5 and GPT-4) research, state-of-the-art large language models (LLM) from the GPT series, and their prospective applications across...

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Automatic statistical diagnosis of COVID-19 based on multi-modal CT feature extraction

Computed tomography (CT) is highly sensitive to lung-related abnormalities as a non-invasive method and has become an essential tool for screening and diagnosing Coronavirus disease 2019 (COVID-19)....

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Extracting functional connectivity brain networks at the resting state from pulsed arterial spin labeling data

Functional connectivity in the brain is often studied with blood oxygenation level dependent (BOLD) resting state functional magnetic resonance imaging (rsfMRI), but the BOLD signal is several steps...

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Medicine-engineering interdisciplinary researches for addiction: Opportunities and challenges

Advances in neuroscience have suggested that addiction is not only an ongoing dynamic transaction between the person, their behavior, and the environment, but a disturbance of neurotransmitters in neurons...

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Significant enhancement of occluded segment on magnetic resonance imaging predicts severe stenosis in atherosclerotic occlusion

The difficulty of recanalization for intracranial atherosclerosis–related large vessel occlusion (ICAS-LVO) is closely related to the severity of stenosis. This study sought to investigate the characteristics...

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Simultaneously acquired rSUV and rCBF of 18F-FDG/MRI in peritumoral brain zone can help to differentiate the grade of gliomas

The purpose of this study is to investigate the diagnostic performance of the peritumoral brain zone (PBZ) in differentiating glioma grades. This is accomplished by comparing the relative standardized...

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Multimodal radiology AI

The growing armamentarium of artificial intelligence (AI) tools cleared by the United States Food and Drug Administration mostly target a narrow, single imaging modality or data source of information....

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A comprehensive survey of ChatGPT: Advancements, applications, prospects, and challenges

Large Language Models (LLMs) especially when combined with Generative Pre-trained Transformers (GPT) represent a groundbreaking in natural language processing. In particular, ChatGPT, a state-of-the-art...

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Application of omics-based biomarkers in substance use disorders

Substance use disorder (SUD) is a type of addictive encephalopathy resulting from drug abuse, which leads to abnormal cerebral alterations indicating neurotoxicity that is manifested through various...

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When brain-inspired AI meets AGI

Artificial General Intelligence (AGI) has been a long-standing goal of humanity, with the aim of creating machines capable of performing any intellectual task that humans can do. To achieve this, AGI...

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The impact of ChatGPT and LLMs on medical imaging stakeholders: Perspectives and use cases

This study investigates the transformative potential of Large Language Models (LLMs), such as OpenAI ChatGPT, in medical imaging. With the aid of public data, these models, which possess remarkable...

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A review of uncertainty estimation and its application in medical imaging

The use of AI systems in healthcare for the early screening of diseases is of great clinical importance. Deep learning has shown great promise in medical imaging, but the reliability and trustworthiness...

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