The evolving landscape of BPH surgical treatments: considering semen parameters in clinical decision-making
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Best of 2024 in Prostate Cancer and Prostatic diseases
Introduction The year 2024 has been transformative for prostate cancer (PCa) and prostatic diseases, marked by advancements in basic science, diagnostic tools and novel therapeutic…
Surgical video workflow analysis via visual-language learning
Surgical video workflow analysis has made intensive development in computer-assisted surgery by combining deep learning models, aiming to enhance surgical scene analysis and decision-making. However, previous research has primarily focused on coarse-grained analysis of surgical videos, e.g., phase recognition, instrument recognition, and triplet recognition that only considers relationships within surgical triplets. In order to provide a more comprehensive fine-grained analysis of surgical videos, this work focuses on accurately identifying triplets <instrument, verb, target> from surgical videos. Specifically, we propose a vision-language deep learning framework that incorporates intra- and inter- triplet modeling, termed I2TM, to explore the relationships among triplets and leverage the model understanding of the entire surgical process, thereby enhancing the accuracy and robustness of recognition. Besides, we also develop a new surgical triplet semantic enhancer (TSE) to establish semantic relationships, both intra- and inter-triplets, across visual and textual modalities. Extensive experimental results on surgical video benchmark datasets demonstrate that our approach can capture finer semantics, achieve effective surgical video understanding and analysis, with potential for widespread medical applications.
Affective integration in experience, judgment, and decision-making
The role of affect in value-based judgment and decision-making has attracted increasing interest in recent decades. Most previous approaches neglect the temporal dependence of mental states leading to mapping a relatively well-defined, but largely static, feeling state to a behavioral tendency. In contrast, we posit that expected and experienced consequences of actions are integrated over time into a unified overall affective experience reflecting current resources under current demands. This affective integration is shaped by context and continually modulates judgments and decisions. Changes in affective states modulate evaluation of new information (affect-as-information), signal changes in the environment (affect-as-a-spotlight) and influence behavioral tendencies in relation to goals (affect-as-motivation). We advocate for an approach that integrates affective dynamics into decision-making paradigms. This dynamical account identifies the key variables explaining how changes in affect influence information processing may provide us with new insights into the role of affect in value-based judgment and decision-making.
Deep learning-driven semantic segmentation and spatial analysis of quarry relic landscapes using point cloud data: insights from the Shaoxing quarry relics
Quarry relic landscapes hold significant historical and cultural value, yet current research often lacks the depth to understand their complex spatial structure. This study addresses this gap by utilizing 3D point cloud data and deep learning to analyze quarry relic landscapes, focusing on the Shaoxing quarry relics. In this paper, point cloud models of four quarry relic landscapes were established, as well as the performance of the PointNet + + network in segmenting complex and variable quarry relic landscape spaces. Based on the semantic segmentation results, quantitative and clustering analyses were conducted on various landscape elements of the four quarry relics, thereby exploring the cultural value of Shaoxing quarry relic’s heritage. The study demonstrates the following key findings: 1. The feasibility of combining 3D laser scanning and UAV photogrammetry to gather detailed site data for documenting quarry relic landscapes has been proven. 2. The PointNet + + deep learning network is particularly effective for the semantic segmentation of landscape elements associated with quarry relics. 3. The Shaoxing quarry relic exhibits a composite spatial form, with a nearly equal ratio of positive to negative space (approximately 1:1). Plants and bare rocks predominantly occupy the positive space, while rocks and stone pits exhibit the highest heritage value. 4. The development of the QLIM&PMS system has facilitated the comprehensive digitalization of the quarry relic landscape, offering examples and technical support for the preservation and utilization of quarry relic sites.
Contraception decision-making autonomy among adolescent girls and young women in Uganda
We assessed contraception decision-making autonomy among current contraceptive users and interest in self-care-oriented contraception among 2109 sexually-active adolescent girls and young women (AGYW) aged 10–24 years in Uganda. Current contraceptive users were asked about who made the decision to use contraception; those who made the decision on their own were considered to have contraception decision-making autonomy. More than half of AGYW (54.8%, n = 1155) were current contraceptive users; of these, 26.8% (n = 310) made the decision to use contraception on their own. Having contraception discussion with partner prior to contraceptive use (adj. PR = 0.39; 95%CI: 0.32, 0.48) and being currently married (adj. PR = 0.74; 95%CI: 0.56, 0.98) were negatively associated with contraception decision-making autonomy. Fifty-eight percent of AGYW (n = 1213) reported interest in obtaining information on how to access and/or use self-care-oriented contraceptive methods. These findings suggest a need to empower AGYW to not only make but also act on their contraceptive decisions.
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