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ISSN: 2950-1628

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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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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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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Unbiasing fairness evaluation of radiology AI model

Fairness of artificial intelligence and machine learning models, often caused by imbalanced datasets, has long been a concern. While many efforts aim to minimize model bias, this study suggests that...

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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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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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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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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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Vision transformers in multi-modal brain tumor MRI segmentation: A review

Brain tumors have shown extreme mortality and increasing incidence during recent years, which bring enormous challenges for the timely diagnosis and effective treatment of brain tumors. Concretely,...

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A survey of emerging applications of diffusion probabilistic models in MRI

Diffusion probabilistic models (DPMs) which employ explicit likelihood characterization and a gradual sampling process to synthesize data, have gained increasing research interest. Despite their huge...

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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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7T MRI in cerebrovascular disorders: From large artery abnormalities to small vessel disease

There is a growing interest and adoption of 7 Tesla (T) magnetic resonance imaging (MRI) in the field of medicine and research. In the domain of neuroimaging, 7T MRI shows notable advantages over lower...

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A Systematic Evaluation of GPT-4V’s Multimodal Capability for Chest X-ray Image Analysis

This work evaluates GPT-4V’s multimodal capability for medical image analysis, focusing on three representative tasks radiology report generation, medical visual question answering, and medical visual...

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Deep learning-based rigid motion correction for magnetic resonance imaging: A survey

Physiological and physical motions of the subjects, e.g., patients, are the primary sources of image artifacts in magnetic resonance imaging (MRI), causing geometric distortion, blurring, low signal-to-noise...

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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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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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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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The general intelligence of GPT–4, its knowledge diffusive and societal influences, and its governance

Recent breakthroughs in artificial intelligence (AI) research include advancements in natural language processing (NLP) achieved by large language models (LLMs), and; in particular, generative pre–trained...

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Opportunities and challenges in the application of large artificial intelligence models in radiology

Influenced by ChatGPT, artificial intelligence (AI) large models have witnessed a global upsurge in large model research and development. As people enjoy the convenience by this AI large model, more...

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Thoracic CT imaging in obesity: Technical challenges, imaging findings and future outlook

Obesity is a highly prevalent and increasing global medical problem. It is expected that most radiologists will come across computed tomography studies of obese patients in their daily work. Obesity...

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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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Deep learning-based artificial intelligence for assisting diagnosis, assessment and treatment in soft tissue sarcomas

Soft tissue sarcomas (STSs) represent a group of heterogeneous mesenchymal tumors of which are generally classified as per the histopathology. Despite being rare in incidence and prevalence, STSs are...

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Allen Human Brain Atlas and magnetic resonance imaging in schizophrenia

Schizophrenia is among top disability causes worldwide; however, its pathological mechanism is still unclear. In order to advance the research progress on schizophrenia, the Schizophrenia Imaging Lab...

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Magnetic resonance-guided focused ultrasound in intracranial diseases: Clinical applications and future directions

Magnetic resonance-guided focused ultrasound (MRgFUS) is a non-invasive technique for neuroregulation that offers several advantages, including non-invasiveness, no need for general anesthesia requirement,...

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Radio-immunomics in hepatocellular carcinoma: Unraveling the tumor immune microenvironment

Hepatocellular carcinoma (HCC) ranks as the sixth most prevalent and the fourth most lethal malignancy worldwide, frequently manifesting at advanced stages with limited therapeutic options. Despite...

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