A Knowledge-enhanced Two-stage Generative Framework for Medical Dialogue Information Extraction

This paper focuses on term-status pair extraction from medical dialogues (MD-TSPE), which is essential in diagnosis dialogue systems and the automatic scribe of electronic medical records (EMRs). In the past few years, works on MD-TSPE have attracted increasing research attention, especially after the remarkable progress made by generative methods. However, these generative methods output a whole sequence consisting of term-status pairs in one stage and ignore integrating prior knowledge, which demands a deeper understanding to model the relationship between terms and infer the status of each term. This paper presents a knowledge-enhanced two-stage generative framework (KTGF) to address the above challenges. Using task-specific prompts, we employ a single model to complete the MD-TSPE through two phases in a unified generative form: we generate all terms the first and then generate the status of each generated term. In this way, the relationship between terms can be learned more effectively from the sequence containing only terms in the first phase, and our designed knowledge-enhanced prompt in the second phase can leverage the category and status candidates of the generated term for status generation. Furthermore, our proposed special status "not mentioned" makes more terms available and enriches the training data in the second phase, which is critical in the low-resource setting. The experiments on the Chunyu and CMDD datasets show that the proposed method achieves superior results compared to the state-of-the-art models in the full training and low-resource settings.Comment: Published in Machine Intelligence Researc

The matching rule of Panum’s limiting case and its influencing factors

IntroductionPanum’s limiting case is one of the typical configurations of monocular occlusion region. The matching rule of Panum’s limiting case is the key to understanding how monocular occlusion region produces stereopsis. There are currently two main views on the matching rule of Panum’s limiting case, namely double fusion and uniqueness constraint. This paper further discusses its matching mechanism on the basis of previous studies.MethodsIn this study, fold line Panum’s stimuli were used to study the matching rule of Panum’s limiting case. In Experiment 1, fixation position was adopted to present the stimulus in a short time to explore the matching rules in Panum’s limiting case. In Experiment 2, the effect of fixation position on Panum’s limiting case matching results was further investigated.ResultsThe results of Experiment 1 show that when stimuli are presented in a short period of time, the reported result that a single feature in one eye may be matched alternately with two features in the other eye. This matching rule is called “fast alternative matching” in this article. The results of Experiment 2 results show that the position of the fixation could affect the matching result of participants.ConclusionIn conclusion, the matching rule of Panum’s limiting case is fast alternative matching, and the matching result is related to the attention state of the participant. These results not only provide a new perspective for matching rules in Panum’s limiting case, but also show that depth perception results in stereopsis can be influenced by top-down cognitive processing. This study provides a theoretical basis for studying the formation of stereopsis in the monocular region to a certain extent. In summary, the matching rule of Panum’s limiting case is fast alternative matching. In previous studies, the perceived result of double fusion may be caused by fast alternative matching. Also, the matching results are related to the participant’s state of attention, which suggests that the depth perception results of stereopsis are influenced by top-down cognitive processing

Communication-Efficient Stochastic Zeroth-Order Optimization for Federated Learning

Federated learning (FL), as an emerging edge artificial intelligence paradigm, enables many edge devices to collaboratively train a global model without sharing their private data. To enhance the training efficiency of FL, various algorithms have been proposed, ranging from first-order to second-order methods. However, these algorithms cannot be applied in scenarios where the gradient information is not available, e.g., federated black-box attack and federated hyperparameter tuning. To address this issue, in this paper we propose a derivative-free federated zeroth-order optimization (FedZO) algorithm featured by performing multiple local updates based on stochastic gradient estimators in each communication round and enabling partial device participation. Under non-convex settings, we derive the convergence performance of the FedZO algorithm on non-independent and identically distributed data and characterize the impact of the numbers of local iterates and participating edge devices on the convergence. To enable communication-efficient FedZO over wireless networks, we further propose an over-the-air computation (AirComp) assisted FedZO algorithm. With an appropriate transceiver design, we show that the convergence of AirComp-assisted FedZO can still be preserved under certain signal-to-noise ratio conditions. Simulation results demonstrate the effectiveness of the FedZO algorithm and validate the theoretical observations.Comment: This work was accepted to Transaction on Signal Processin

VILAS: Exploring the Effects of Vision and Language Context in Automatic Speech Recognition

Enhancing automatic speech recognition (ASR) performance by leveraging additional multimodal information has shown promising results in previous studies. However, most of these works have primarily focused on utilizing visual cues derived from human lip motions. In fact, context-dependent visual and linguistic cues can also benefit in many scenarios. In this paper, we first propose ViLaS (Vision and Language into Automatic Speech Recognition), a novel multimodal ASR model based on the continuous integrate-and-fire (CIF) mechanism, which can integrate visual and textual context simultaneously or separately, to facilitate speech recognition. Next, we introduce an effective training strategy that improves performance in modal-incomplete test scenarios. Then, to explore the effects of integrating vision and language, we create VSDial, a multimodal ASR dataset with multimodal context cues in both Chinese and English versions. Finally, empirical results are reported on the public Flickr8K and self-constructed VSDial datasets. We explore various cross-modal fusion schemes, analyze fine-grained crossmodal alignment on VSDial, and provide insights into the effects of integrating multimodal information on speech recognition.Comment: Accepted to ICASSP 202

A van der Waals pn heterojunction with organic/inorganic semiconductors

van der Waals (vdW) heterojunctions formed by two-dimensional (2D) materials have attracted tremendous attention due to their excellent electrical/optical properties and device applications. However, current 2D heterojunctions are largely limited to atomic crystals, and hybrid organic/inorganic structures are rarely explored. Here, we fabricate hybrid 2D heterostructures with p-type dioctylbenzothienobenzothiophene (C8-BTBT) and n-type MoS2. We find that few-layer C8-BTBT molecular crystals can be grown on monolayer MoS2 by vdW epitaxy, with pristine interface and controllable thickness down to monolayer. The operation of the C8-BTBT/MoS2 vertical heterojunction devices is highly tunable by bias and gate voltages between three different regimes: interfacial recombination, tunneling and blocking. The pn junction shows diode-like behavior with rectifying ratio up to 105 at the room temperature. Our devices also exhibit photovoltaic responses with power conversion efficiency of 0.31% and photoresponsivity of 22mA/W. With wide material combinations, such hybrid 2D structures will offer possibilities for opto-electronic devices that are not possible from individual constituents.Comment: 16 pages, 4 figure

Gonadotropin-releasing hormone analogue and recombinant human growth hormone treatment for idiopathic central precocious puberty in girls

PurposeTo investigate the effectiveness and safety of gonadotropin-releasing hormone analogue (GnRHa) in combination with recombinant human growth hormone (rhGH) in girls with central precocious puberty (CPP).MethodsClinical data of 80 girls diagnosed with idiopathic central precocious puberty (ICPP) between January 2017 and June 2021 were retrospectively analyzed. Treatment strategy involved GnRHa alone (group A: n=34) and GnRHa+rhGH (group B: n=46). Children’s heights (Ht), weights (Wt) and sex hormone levels were measured every 3 months after treatment and bone age (BA) every six months. Heights, growth velocity (GV), predicted adult height (PAH), weights, body mass index (BMI), sex hormone levels and bone age were compared between the two groups.ResultsChildren in group B showed greater height gain at the 12th, 24th and 30th months after treatment (p<0.05) than those in group A, had faster growth rates in the first and second year following treatment (p<0.05) and better PAH (p<0.05). No statistical differences in weight or BMI were found between the two groups before treatment or at any time after treatment (p>0.05). Levels of LH and FSH were lower in both groups after treatment with no statistical differences between groups (p>0.05). The gap between bone age and chronological age gradually decreased in both groups and no abnormal progression of bone age or other adverse side effects occurred.ConclusionsThe combination of GnRHa with rhGH produced better height gains than GnRHa alone for patients with CPP. The gonadal axis was suppressed and progression of bone age delayed with good safety and efficacy

Scan-free direct measurement of an extremely high-dimensional photonic state

Retrieving the vast amount of information carried by a photon is an enduring challenge in quantum metrology science and quantum photonics research. The transverse spatial state of a photon is a convenient high-dimensional quantum system for study, as it has a well-understood classical analog as the transverse complex field profile of an optical beam. One severe drawback of all currently available quantum metrology techniques is the need for a time-consuming characterization process, which scales very unfavorably with the dimensionality of the quantum system. Here we demonstrate a technique that directly measures a million-dimensional photonic spatial state with a single setting of the measurement apparatus. Through the arrangement of a weak measurement of momentum and parallel strong measurements of position, the complex values of the entire photon state vector become measurable directly. The dimension of our measured state is approximately four orders of magnitude larger than previously measured. Our work opens up a practical route for characterizing high-dimensional quantum systems in real time. Furthermore, our demonstration also serves as a high-speed, extremely high-resolution unambiguous complex field measurement technique for diverse classical applications

Mean Platelet Volume and Platelet Distribution Width as Markers in the Diagnosis of Acute Gangrenous Appendicitis

Introduction. Acute gangrenous appendicitis (AGA) is a common medical condition; however, the grade of appendicitis usually cannot be established preoperatively. We have attempted to identify some indicators, such as the mean platelet volume (MPV) and the platelet distribution width (PDW), to diagnose AGA. Aims. To evaluate whether or not the MPV and PDW are suitable markers to diagnose AGA. Methods. A retrospective study of 160 patients with AGA and 160 healthy patients was undertaken. Disease diagnosis was confirmed based on the pathologic examination of surgical specimens. Patient white blood cell (WBC) count, neutrophil ratio (NR), platelet (PLT) count, MPV, PDW, and hematocrit (HCT) were analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the sensitivity and specificity of these indices in AGA. Results. There were no significant differences between the AGA and control groups in age and gender. Compared to the control group, the WBC count, NR, and PDW were significantly higher ( < 0.001, resp.) and the MPV and HCT were significantly lower ( < 0.001, resp.) in the AGA group. The diagnostic specificities of the WBC count, NR, PLT count, MPV, PDW, and HCT were 86.3%, 92.5%, 58.1%, 81.7%, 83.9%, and 66.3%, respectively. Therefore, the NR had the highest diagnostic specificity for the diagnosis of AGA. Conclusions. This is the first study to assess the MPV and PDW in patients with AGA. Our present study showed that the MPV is reduced and the PDW is increased in patients with AGA; the sensitivity of PDW was superior to the MPV. A decreased MPV value and an increased PDW could serve as two markers to diagnose AGA. The NR had the highest specificity for the diagnosis of AGA