Advancing Medical Imaging with Language Models: A Journey from N-grams to ChatGPT

In this paper, we aimed to provide a review and tutorial for researchers in the field of medical imaging using language models to improve their tasks at hand. We began by providing an overview of the history and concepts of language models, with a special focus on large language models. We then reviewed the current literature on how language models are being used to improve medical imaging, emphasizing different applications such as image captioning, report generation, report classification, finding extraction, visual question answering, interpretable diagnosis, and more for various modalities and organs. The ChatGPT was specially highlighted for researchers to explore more potential applications. We covered the potential benefits of accurate and efficient language models for medical imaging analysis, including improving clinical workflow efficiency, reducing diagnostic errors, and assisting healthcare professionals in providing timely and accurate diagnoses. Overall, our goal was to bridge the gap between language models and medical imaging and inspire new ideas and innovations in this exciting area of research. We hope that this review paper will serve as a useful resource for researchers in this field and encourage further exploration of the possibilities of language models in medical imaging

Text Alignment Is An Efficient Unified Model for Massive NLP Tasks

Large language models (LLMs), typically designed as a function of next-word prediction, have excelled across extensive NLP tasks. Despite the generality, next-word prediction is often not an efficient formulation for many of the tasks, demanding an extreme scale of model parameters (10s or 100s of billions) and sometimes yielding suboptimal performance. In practice, it is often desirable to build more efficient models -- despite being less versatile, they still apply to a substantial subset of problems, delivering on par or even superior performance with much smaller model sizes. In this paper, we propose text alignment as an efficient unified model for a wide range of crucial tasks involving text entailment, similarity, question answering (and answerability), factual consistency, and so forth. Given a pair of texts, the model measures the degree of alignment between their information. We instantiate an alignment model (Align) through lightweight finetuning of RoBERTa (355M parameters) using 5.9M examples from 28 datasets. Despite its compact size, extensive experiments show the model's efficiency and strong performance: (1) On over 20 datasets of aforementioned diverse tasks, the model matches or surpasses FLAN-T5 models that have around 2x or 10x more parameters; the single unified model also outperforms task-specific models finetuned on individual datasets; (2) When applied to evaluate factual consistency of language generation on 23 datasets, our model improves over various baselines, including the much larger GPT-3.5 (ChatGPT) and sometimes even GPT-4; (3) The lightweight model can also serve as an add-on component for LLMs such as GPT-3.5 in question answering tasks, improving the average exact match (EM) score by 17.94 and F1 score by 15.05 through identifying unanswerable questions.Comment: NeurIPS 2023 Camera Ready, Code available at https://github.com/yuh-zha/Alig

Disruption of the Gene Encoding Endo-β-1, 4-Xylanase Affects the Growth and Virulence of Sclerotinia sclerotiorum

Sclerotinia sclerotiorum (Lib.) de Bary is a devastating fungal pathogen with worldwide distribution. S. sclerotiorum is a necrotrophic fungus that secretes many cell wall-degrading enzymes (CWDEs) that destroy plant’s cell-wall components. Functional analyses of the genes that encode CWEDs will help explain the mechanisms of growth and pathogenicity of S. sclerotiorum. Here, we isolated and characterized a gene SsXyl1 that encoded an endo-β-1, 4-xylanase in S. sclerotiorum. The SsXyl1 expression showed a slight increase during the development and germination stages of sclerotia and a dramatic increase during infection. The expression of SsXyl1 was induced by xylan. The SsXyl1 deletion strains produce aberrant sclerotia that could not germinate to form apothecia. The SsXyl1 deletion strains also lost virulence to the hosts. This study demonstrates the important roles of endo-β-1, 4-xylanase in the growth and virulence of S. sclerotiorum

Comprehensive Analysis, Discussion and Suggestion on the Current Situation of Cardiopulmonary Resuscitation and Automatic External Defibrillator in General Public in China

The number of sudden cardiac death (SCD) has increased year by year, which has become one of the main causes of death in China. Timely cardiopulmonary resuscitation (CPR) and timely and accurate use of automatic external defibrillator (AED) can greatly improve the survival rate of patients with sudden cardiac death. Because the large probability of sudden cardiac death occurs outside the hospital, it is very important for the general public to master first aid skills. This paper will mine all kinds of data from multi-dimensional and multi-angle, analyze the mastery of public first aid skills in China, and provide practical suggestions and ideas for popularizing first aid skills in the future

Molecular state interpretation of charmed baryons in the quark model

Stimulated by the observation of $\Lambda_c(2910)^+$ by the Belle Collaboration, the $S$-wave $qqq\bar{q}c~(q=u~\text{or}~d)$ pentaquark systems with $I$ = 0, $J^P$ = $\frac{1}{2}^-,~\frac{3}{2}^- and~\frac{5}{2}^-$ are investigated in the framework of quark delocalization color screening model(QDCSM). The real-scaling method is utilized to check the bound states and the genuine resonance states. The root mean square of cluster spacing is also calculated to study the structure of the states and estimate if the state is resonance state or not. The numerical results show that $\Lambda_{c}(2910)$ cannot be interpreted as a molecular state, and $\Sigma_{c}(2800)$ cannot be explained as the $ND$ molecular state with $J^P=1/2^-$. $\Lambda_{c}(2595)$ can be interpreted as the molecular state with $J^P=\frac{1}{2}^-$ and the main component is $\Sigma_{c}\pi$. $\Lambda_{c}(2625)$ can be interpreted as the molecular state with $J^P=\frac{3}{2}^-$ and the main component is $\Sigma_{c}^{*}\pi$. $\Lambda_{c}(2940)$ is likely to be interpreted as a molecular state with $J^P=3/2^-$, and the main component is $ND^{*}$. Besides, two new molecular states are predicted, one is the $J^P=3/2^-$ $\Sigma_{c}\rho$ resonance state with the mass around 3140 MeV, another one is the $J^P=\frac{5}{2}^-$ $\Sigma_{c}^*\rho$ with the mass of 3188.3 MeV.Comment: 12 pages, 3 figure

Seeing the Unheard: dynamics of thin liquid film in holographic ultrasonic field revealed by time-resolved Schlieren imaging

In this study, we introduce a unique approach that employs time-resolved Schlieren imaging to capture and visualize the dynamic changes of a thin liquid (mixture of water, soap and glycerin) film in ultrasonic wave field with high spatial and temporal resolution. By placing a soap film spanning a wire frame vertically in the path of light, we harnessed the vibrations induced by the ultrasonic waves, resulting in remarkable Schlieren imaging patterns. The investigation not only uncovers an unexpected branch flow phenomenon within the film, challenging existing assumptions, but also reveals a fascinating interplay between vortex flow and branch flow. The experiments have revealed a captivating spectrum of dynamic phenomena within the thin liquid films. The observation of small-scale capillary waves, large-scale standing waves, traveling waves, and the intricate fusion of capillary-gravity wave patterns underscores the rich complexity inherent in the interaction between the films and the holographic ultrasonic wave field. These diverse states of film dynamics provide a comprehensive understanding of the intricate interplay between various wave modes and fluid behavior, further enhancing comprehension of this fascinating phenomenon. The ability to visualize the pressure field opens up new avenues for optimizing acoustic levitation techniques, investigating particle behavior, and exploring potential applications in materials science and bioengineering.Comment: 10 pages, 8 page