Hasil untuk "Sports medicine"

D. Harriss, G. Atkinson

Joshua D. Harris, Carmen E. Quatman, M. M. Manring et al.

Kayode Makinde, Oluwatimileyin Onasanya, Frances Adelakun

This study examines whether following popular Nigerian sports betting influencers on social media is a financially sound strategy. To avoid the survivorship bias that occurs when influencers only share their winning bets, we tracked 5,467 pre-match betting slips from three prominent tipsters on X (formerly Twitter) and Telegram. We verified the outcomes against official Stake.com records, resulting in a final dataset covering approximately $4.8 million in tracked bets. We analyzed raw performance, assessed risk based on odds sizes, and applied four common staking strategies (Flat, Inverse, Square Root, and Fixed Return) to simulate realistic follower outcomes. The results show a sharp contrast between the wealth these influencers display online and the actual financial results. The influencers themselves collectively lost 25.24% on their promoted bets, while a follower who staked the same amount on every tip would lose 38.27% on their investment. Across all tested strategies, following these influencers consistently led to significant financial losses. These findings raise serious consumer protection concerns in Nigeria's expanding gambling market.

Erdal Horata, Emel Taşvuran Horata, Arife Nur Kanyilmaz et al.

Abstract Background Tissue flossing and mobilization with movement (MWM) have been used to improve ankle dorsiflexion range of motion (ROM), vertical jump, gait, and balance in athletes after sports injuries or to increase sports performance. However, direct comparisons between tissue flossing and MWM in recreationally active, healthy young adults remain limited. This study aimed to compare the effects of tissue flossing and MWM on ankle ROM, jump, gait, and balance in recreationally active young adults. The secondary aim was to compare the perceived comfort level between interventions. Methods This crossover randomized controlled study included three groups: Flossing, MWM, and control. The interventions were administered with a one-week interval between sessions. The tissue flossing and the MWM were applied to both ankles. No intervention was performed in the control group. All measurements were conducted both before and after the interventions. Passive and active ankle dorsiflexion ROM was evaluated using ImageJ software and the Weight-Bearing Lunge Test, respectively. The BTS G-Walk IMU sensor was used for counter-movement jump, gait, and balance assessments. Results Two-way repeated-measures ANOVA revealed significant group × time interaction effects for passive ankle dorsiflexion ROM and jump height (p < 0.05), with the MWM group showing greater improvements than the flossing and control groups. Active ankle dorsiflexion ROM also showed a significant interaction effect (p < 0.05), where both the MWM and flossing groups improved compared to the control group. Within-group comparisons showed no improvement in the control group (p > 0.05). The MWM group demonstrated significant gains in both active and passive dorsiflexion ROM and vertical jump height (p < 0.05), whereas the flossing group improved only in active dorsiflexion ROM (p < 0.05). The MWM was also perceived as more comfortable than flossing (p < 0.05). Conclusions MWM demonstrated advantages in specific outcomes (passive ROM, jump height, comfort) compared to flossing in the acute setting. Trial registration NCT06392880, 04/26/2024 (retrospectively registered), Link https//clinicaltrials.gov/study/NCT06392880.

Anbang Du, Michael Head, Markus Brede

Interdisciplinary research, a process of knowledge integration, is vital for scientific advancements. It remains unclear whether prestigious journals that are highly impactful lead in disseminating interdisciplinary knowledge. In this paper, by constructing topic-level correlation networks based on publications, we evaluated the interdisciplinarity of more and less prestigious journals in medicine. We found research from prestigious medical journals tends to be less interdisciplinary than research from other medical journals. We also established that cancer-related research is the main driver of interdisciplinarity in medical science. Our results indicate a weak tendency for differences in topic correlations between more and less prestigious journals to be co-located. Accordingly, we identified that interdisciplinarity in prestigious journals mainly differs from interdisciplinarity in other journals in areas such as infections, nervous system diseases and cancer. Overall, our results suggest that interdisciplinarity in science could benefit from prestigious journals easing rigid disciplinary boundaries.

Yu Cheng, Harun Šiljak

Accurate, real-time collision detection is essential for ensuring player safety and effective refereeing in high-contact sports such as rugby, particularly given the severe risks associated with traumatic brain injuries (TBI). Traditional collision-monitoring methods employing fixed cameras or wearable sensors face limitations in visibility, coverage, and responsiveness. Previously, we introduced a framework using unmanned aerial vehicles (UAVs) for monitoring and real time kinematics extraction from videos of collision events. In this paper, we show that the strategies operating on the objective of ensuring at least one UAV captures every incident on the pitch have an emergent property of fulfilling a stronger key condition for successful kinematics extraction. Namely, they ensure that almost all collisions are captured by multiple drones, establishing multi-view fidelity and redundancy, while not requiring any drone-to-drone communication.

Puntawat Ponglertnapakorn, Supasorn Suwajanakorn

We present a method for 3D ball trajectory estimation from a 2D tracking sequence. To overcome the ambiguity in 3D from 2D estimation, we design an LSTM-based pipeline that utilizes a novel canonical 3D representation that is independent of the camera's location to handle arbitrary views and a series of intermediate representations that encourage crucial invariance and reprojection consistency. We evaluated our method on four synthetic and three real datasets and conducted extensive ablation studies on our design choices. Despite training solely on simulated data, our method achieves state-of-the-art performance and can generalize to real-world scenarios with multiple trajectories, opening up a range of applications in sport analysis and virtual replay. Please visit our page: https://where-is-the-ball.github.io.

Menghua Xia, Reimund Bayerlein, Yanis Chemli et al.

Artificial intelligence-generated content (AIGC) has shown remarkable performance in nuclear medicine imaging (NMI), offering cost-effective software solutions for tasks such as image enhancement, motion correction, and attenuation correction. However, these advancements come with the risk of hallucinations, generating realistic yet factually incorrect content. Hallucinations can misrepresent anatomical and functional information, compromising diagnostic accuracy and clinical trust. This paper presents a comprehensive perspective of hallucination-related challenges in AIGC for NMI, introducing the DREAM report, which covers recommendations for definition, representative examples, detection and evaluation metrics, underlying causes, and mitigation strategies. This position statement paper aims to initiate a common understanding for discussions and future research toward enhancing AIGC applications in NMI, thereby supporting their safe and effective deployment in clinical practice.

Nengyue Su, Liang Luo, Yu Gu et al.

The rise of autonomous driving technology has led to concerns about inactivity-induced fatigue. This paper explores Traditional Chinese Medicine (TCM) scents for mitigating. Two human-involved studies have been conducted in a high-fidelity driving simulator. Study 1 maps six prevalent TCM scents onto the arousal/valence circumplex to select proper candidates, i.e., argy wormwood (with the highest arousal) and tangerine peel (with the highest valence). Study 2 tests both scents in an auto-driving course. Statistics show both scents can improve driver alertness and reaction-time, but should be used in different ways: argy wormwood is suitable for short-term use due to its higher intensity but poor acceptance, while tangerine peel is ideal for long-term use due to its higher likeness. These findings provide insights for in-car fatigue mitigation to enhance driver safety and well-being. However, issues such as scent longevity as for aromatherapy and automatic fatigue prediction remain unresolved.

Shao M, Ni L, Jiang L et al.

Min Shao,1,&amp;ast; Lijia Ni,2,3,&amp;ast; Liang Jiang,4 Jingyi Hou,4 Sicheng Xu,4 Yin Lin,5 Xiaoying Xie6 1Department of Pharmacy, Liwan Central Hospital of Guangzhou, Guangzhou, 510000, People’s Republic of China; 2Department of Clinical Laboratory, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, People’s Republic of China; 3Institution of Antibiotic, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, People’s Republic of China; 4Department of Orthopedic Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, People’s Republic of China; 5Department of Pharmacy, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, People’s Republic of China; 6Department of Clinical Laboratory, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, 518106, People’s Republic of China&amp;ast;These authors contributed equally to this workCorrespondence: Xiaoying Xie, Email xiexy5@mail.sysu.edu.cn Yin Lin, Email linyin@mail.sysu.edu.cnAbstract: Mycobacterium wolinskyi (M. wolinskyi), which is a rare rapidly growing mycobacterium (RGM), and the infections it causes are predominantly linked to surgery or invasive procedures. We detailed a case of refractory surgical site infection (SSI) caused by M. wolinskyi. The causative pathogen was identified by metagenomic next-generation sequencing (mNGS) analysis, 16S rRNA and rpoB gene sequencing. What renders this case particularly remarkable is the complexity introduced by a series of antibiotic-induced adverse effects, which seem to be deeply intertwined with the patient’s underlying metabolic syndrome. With the meticulous pharmaceutical guidance provided by the clinical pharmacist, the patient experienced a substantial improvement in his knee joint infection.Keywords: Mycobacterium wolinskyi, surgical site infection, metabolic syndrome, mNGS

D. Clark, Amar Parikh, J. M. Dendy et al.

1Vanderbilt University Medical Center, Division of Cardiovascular Medicine, Department of Internal Medicine, Nashville, TN; 2Vanderbilt University Medical Center, Department of Orthopaedic Surgery and Sports Medicine, Nashville, TN; 3Monroe Carell Jr. Children’s Hospital at Vanderbilt, Thomas P. Graham Division of Pediatric Cardiology, Department of Pediatrics, Nashville, TN; 4Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN *Co-senior authors listed in alphabetical order * Drs. Hughes and Soslow contributed equally as co-senior authors.

A. Anandacoomarasamy, L. Barnsley

Huifeng Wang, S. Kadry, Ebin Deni Raj

Abstract Nowadays, wearable techniques are widely used in the Internet of Things (IoT). The discussed IoT devices are used in various applications such as smart home, security management, education institutions and so on. Among the various application, IoT devices are used widely in health care application for reducing the risk factors. So, in this paper, introduces the wearable sensors based on the Internet of Things (WS-IoT) for sports person continuous health monitoring system. The goal of this paper is to define the health clinics for sports medicine and performance services of the sports team to further the use of the technology to help athletes return to play in different fields of sport. With the help of wearable tracking devices to collect the health details and track the exercise records. To analyze and monitoring sports person health effective optimization machine learning techniques are introduced. The created system efficiency is evaluated using experimental results and discussion.

Aaron L. Sarvet, Mats J. Stensrud

In our original article (Sarvet & Stensrud, 2024), we examine twin definitions of "harm" in personalized medicine: one based on predictions of individuals' unmeasurable response types (counterfactual harm), and another based solely on the observations of experiments (interventionist harm). In their commentary, Mueller & Pearl (2024) (MP) read our review as an argument that "counterfactual logic should [...] be purged from consideration of harm and benefit" and "strongly object [...] that a rational decision maker may well apply the interventional perspective to the exclusion of counterfactual considerations." Here we show that this objection is misguided. We analyze MP's examples and derive a general result, showing that determinations of harm through interventionist and counterfactual analyses will always concur. Therefore, individuals who embrace counterfactual formulations and those who object to their use will make equivalent decisions in uncontroversial settings.

Ryota Tanaka, Tomohiro Suzuki, Keisuke Fujii

Understanding human actions from videos is essential in many domains, including sports. In figure skating, technical judgments are performed by watching skaters' 3D movements, and its part of the judging procedure can be regarded as a Temporal Action Segmentation (TAS) task. TAS tasks in figure skating that automatically assign temporal semantics to video are actively researched. However, there is a lack of datasets and effective methods for TAS tasks requiring 3D pose data. In this study, we first created the FS-Jump3D dataset of complex and dynamic figure skating jumps using optical markerless motion capture. We also propose a new fine-grained figure skating jump TAS dataset annotation method with which TAS models can learn jump procedures. In the experimental results, we validated the usefulness of 3D pose features as input and the fine-grained dataset for the TAS model in figure skating. FS-Jump3D Dataset is available at https://github.com/ryota-skating/FS-Jump3D.

Li Yizhen, Huang Shaohan, Qi Jiaxing et al.

No previous work has studied the performance of Large Language Models (LLMs) in the context of Traditional Chinese Medicine (TCM), an essential and distinct branch of medical knowledge with a rich history. To bridge this gap, we present a TCM question dataset named TCM-QA, which comprises three question types: single choice, multiple choice, and true or false, to examine the LLM's capacity for knowledge recall and comprehensive reasoning within the TCM domain. In our study, we evaluate two settings of the LLM, zero-shot and few-shot settings, while concurrently discussing the differences between English and Chinese prompts. Our results indicate that ChatGPT performs best in true or false questions, achieving the highest precision of 0.688 while scoring the lowest precision is 0.241 in multiple-choice questions. Furthermore, we observed that Chinese prompts outperformed English prompts in our evaluations. Additionally, we assess the quality of explanations generated by ChatGPT and their potential contribution to TCM knowledge comprehension. This paper offers valuable insights into the applicability of LLMs in specialized domains and paves the way for future research in leveraging these powerful models to advance TCM.

SC Weber, J Pallas, G Olson et al.

STARR (STAnford Research Repository) is a clinical research support ecosystem that supports basic science research, population health research and translational research at Stanford University. STARR consists of raw and analysis ready multi-modal data, and tools for cohort analysis and self service data access. STARR data is accessible on secure shared computing systems for ad hoc analysis. Also present is a suite of services on top of STARR, that allow researchers access to complex purpose built data cuts, common data models and software solutions. This manuscript is a research resource description and describes the evolution of STARR Tools that are used to offer self-service access to detailed clinical data for research purposes to researchers at Stanford Medicine, along with a framework used to ensure that data acquired via the self-service tools is handled in compliance with all applicable regulations and rules.

Arman Rahmim, Tyler J. Bradshaw, Guido Davidzon et al.

The 2nd SNMMI Artificial Intelligence (AI) Summit, organized by the SNMMI AI Task Force, took place in Bethesda, MD, on February 29 - March 1, 2024. Bringing together various community members and stakeholders, and following up on a prior successful 2022 AI Summit, the summit theme was: AI in Action. Six key topics included (i) an overview of prior and ongoing efforts by the AI task force, (ii) emerging needs and tools for computational nuclear oncology, (iii) new frontiers in large language and generative models, (iv) defining the value proposition for the use of AI in nuclear medicine, (v) open science including efforts for data and model repositories, and (vi) issues of reimbursement and funding. The primary efforts, findings, challenges, and next steps are summarized in this manuscript.

Sebastian Lappen, Sebastian Siebenlist, Tim Leschinger et al.

Chit K. Leung, Joshua D.K. Bernal, Angus P. Yu et al.

Background/Objective: This study aims to examine the comparative effects of 75 min of volume-matched once-weekly and thrice-weekly high-intensity interval training (HIIT) on body adiposity in adults with central obesity. Methods: This assessor-blinded, three-arm, randomized controlled trial will recruit 315 physically inactive adults with central obesity (aged ≥18 years, body mass index ≥23, waist circumference ≥90 cm for men and ≥80 cm for women). Participants will be randomly allocated to the once-weekly HIIT, thrice-weekly HIIT or usual care control group. Participants in the HIIT groups will receive weekly exercise training sessions for 16 weeks, prescribed either once or three times weekly. Each HIIT session will consist of a supervised program of four 4-min high-intensity intervals at 85%–95% peak heart rate (HRpeak) interspersed with 3-min active recovery intervals at 50%–70% HRpeak. Participants in the once-weekly HIIT group will perform the 25-min HIIT bout three times with a break between each 25-min HIIT bout. The usual care control group will receive bi-weekly health education classes. The outcome assessments will be conducted at baseline, 16 weeks (post-intervention) and 32 weeks (follow-up). The primary outcome will be total body adiposity assessed by dual-energy X-ray absorptiometry (DXA). The secondary outcome measures will include markers of cardiovascular and metabolic health (body composition, cardiorespiratory fitness, blood pressure, and blood lipids), mental health, cognitive performance, health-related quality of life, sleep quality, habitual physical activity, diet, medication, adverse events and adherence to the intervention. Impact of the project: The findings from this study are expected to consolidate the therapeutic efficacy of HIIT for the management of central obesity and inform the comparative compliance, feasibility and suitability of once-weekly and thrice-weekly HIIT as exercise strategies to manage obesity. In particular, the present study is expected to provide a novel perspective on the utility of low-frequency HIIT (i.e., once-weekly) as an effective and sustainable exercise strategy to tackle the obesity pandemic. The anticipated findings will hold substantial translational value by informing public health policies and enhancing exercise compliance in the physically inactive obese population. Trial registration: ClinicalTrials.gov (NCT04887454).