Artificial Intelligence–Enabled ECG Screening for LVSD in LBBB by Hak Seung Lee, MD, Sooyeon Lee, MD, Sora Kang, MS, Ga In Han, MS, Ah-Hyun Yoo, MS, Jong-Hwan Jang, PhD, Yong-Yeon Jo, PhD, Jeong Min Son, MD, Min Sung Lee, MD, MS, Joon-myoung Kwon, MD, MS, Kyung-Hee Kim, MD, PhD

“…Conclusions: Our findings indicate that a broad AI-ECG model reliably detects LVSD in LBBB patients, and transfer learning offers modest improvements without requiring curated LBBB data sets. …”
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Multiclass skin lesion classification and localziation from dermoscopic images using a novel network-level fused deep architecture and explainable artificial intelligence by Mehak Arshad, Muhammad Attique Khan, Nouf Abdullah Almujally, Areej Alasiry, Mehrez Marzougui, Yunyoung Nam

“…Abstract Background and objective Early detection and classification of skin cancer are critical for improving patient outcomes. …”
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Socioeconomic deprivation and regional variation in Hodgkin’s lymphoma incidence in the UK: a population-based cohort study of 10 million individuals by Georgios Lyratzopoulos, Sara Thomas, Andrew Hayward, Charlotte Warren-Gash, Meena Rafiq, S Denaxas, Arturo Gonzalez-Izquierdo

“…This nationwide study conducted over a 25-year period in the UK investigates variation in HL incidence by age, sex, region and deprivation to identify trends and high-risk populations for HL development.Design Population-based cohort study.Setting Clinical Practice Research Datalink (CPRD) electronic primary care records linked to Hospital Episode Statistics and Index of Multiple Deprivation data were used.Participants Data on 10 million individuals in the UK from 1992 to 2016 were analysed.Primary and secondary outcome measures Poisson models were used to explore differences in HL incidence by age, sex, region and deprivation. …”
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A Hypertrophic Distal Fascicle of the Anterior Tibiofibular Ligament is Associated with a High Rate of Osteochondral Lesions of the Talus by James J. Butler MB BCh BAO, Grace W. Randall BS, Miki Dalmau-Pastor PhD, Charles Lin MD, Lauren Schoof MD, John G. Kennedy MD, MCh, MMSc, FFSEM, FRCS (Orth)

“…However, the clinical manifestations of these OCLs in the setting of a hypertrophic ATiFLdf has not been described to date. …”
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Collaborative assessment of the risk of postoperative progression in early-stage non-small cell lung cancer: a robust federated learning model by Yu Liu, Xiaobei Duan, Xiaojuan Chen, Kunwei Li, Qiong Li, Ke Liu, Wansheng Long, Huan Lin, Bao Feng, Xiangmeng Chen

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A hybrid setup for rodent hyperpolarized metabolic imaging using a clinical magnetic resonance scanner by Ditte Bentsen Christensen, Ingeborg Sæten Skre, Jan Henrik Ardenkjær-Larsen, Mor Mishkovsky, Mathilde H Lerche

“…We detail the experimental procedure, provide practical guidance, and showcase the capabilities of the system with example data from mouse brain imaging.This hybrid setup bridges the gap between clinical and pre-clinical research, enabling iterative testing of equipment, imaging sequences, and hypotheses across phantoms, in vivo rodent models and clinical settings. …”
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Impact of adding carboplatin to docetaxel chemotherapy on testosterone levels and treatment outcomes in metastatic docetaxel-resistant prostate cancer by Hejar Atalan, Michael A. Morgan, Philipp Ivanyi, Paula Kappler, Florian H. Heidel, Christoph W. M. Reuter

“…Low FT was an independent predictor for better PFS and for improved OS in groups 1 and 2. Our data indicate that adding carboplatin may improve the therapeutic effects of docetaxel in a castration-dependent setting.…”
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Accurate diagnosis of ischemic heart disease without exposure to radiation using non-stress unshielded magnetocardiography by Kirsten Tolstrup, Massoud Akhtari, Donatella Brisinda, Anna M. Meloni, Robert J. Siegel, Riccardo Fenici

“…., 9 and 36 channels) in a general clinical setting. Scan time was 90 s to 6 min. Interventions: The MCG data were processed with the same automated analysis software and results were immediately available. …”
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Machine learning and explainable artificial intelligence to predict and interpret lead toxicity in pregnant women and unborn baby by Priyanka Chaurasia, Pratheepan Yogarajah, Abbas Ali Mahdi, Sally McClean, Mohammad Kaleem Ahmad, Tabrez Jafar, Sanjay Kumar Singh

“…To address this limitation, our previous research proposed a novel machine learning (ML)-based model that predicts lead exposure levels in pregnant women using sociodemographic data alone. However, for such predictive models to gain broader acceptance, especially in clinical and public health settings, transparency and interpretability are essential.MethodsUnderstanding the reasoning behind the predictions of the model is crucial to building trust and facilitating informed decision-making. …”
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Reevaluating Pediatric Osteomyelitis with Osteoarticular Tuberculosis: Addressing Diagnostic Delays and Improving Treatment Outcomes by Alexandru Herdea, Harun Marie, Ioana-Alexandra Negrila, Aliss Delia Abdel Hamid Ahmed, Alexandru Ulici

“…Background: Pediatric osteoarticular tuberculosis (TB) remains a significant global health challenge, particularly in resource-limited settings, where delayed diagnosis and treatment frequently lead to severe long-term complications. …”
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Energy-Efficient Wireless Multimedia Sensor Nodes for Plant Proximal Monitoring by Daniele Trinchero, Giovanni Paolo Colucci, Elena Filipescu, Ussama Syed Muhammad Zafar, Paola Battilani

“…Via the LoRaWAN downlink, it is possible to efficiently control the camera settings; the shooting times and periodicity, according to weather conditions; the eventual farming operations; the crop growth stages and the season. …”
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Prospective Study of Dobutamine Stress Echocardiography in Comparison with 18F-fluorodeoxyglucose Positron Emission Tomography for Myocardial Viability in Ischemic Cardiomyopathy by Nuthalapati Rama Kumari, Arumulla Sunitha, Sama Rajashekhar

“…The statistical software SPSS 17.0 version was used in the analysis of the data. Results: In our study population, the mean LV ejection fraction was 35.1%. …”
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Drone hyperspectral imaging and artificial intelligence for monitoring moss and lichen in Antarctica by Juan Sandino, Johan Barthelemy, Ashray Doshi, Krystal Randall, Sharon A. Robinson, Barbara Bollard, Felipe Gonzalez

“…This study investigates the potential of hyperspectral imaging (HSI) for mapping cryptogamic vegetation and presents a workflow combining UAVs, ground observations, and machine learning (ML) classifiers. Data collected during a 2023 summer expedition to Antarctic Specially Protected Area 135, East Antarctica, were used to evaluate 12 configurations derived from five ML models, including gradient boosting (XGBoost, CatBoost) and convolutional neural networks (CNNs) (G2C-Conv2D, G2C-Conv3D, and UNet), tested with full and light input feature sets. …”
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EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach by Eyad Talal Attar

“…The integration of EEG biomarkers with machine learning methods emerges as a potential pathway for real-time cognitive and emotional state monitoring which enables tailored interventions through neurofeedback systems and brain–computer interfaces to boost cognitive function and emotional health across clinical settings and everyday life.…”
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The function and significance of SELENBP1 downregulation in human bronchial epithelial carcinogenic process. by Gu-Qing Zeng, Hong Yi, Peng-Fei Zhang, Xin-Hui Li, Rong Hu, Mao-Yu Li, Cui Li, Jia-Quan Qu, Xingming Deng, Zhi-Qiang Xiao

“…<h4>Conclusions</h4>The present data shows for the first time that decreased SELENBP1 is an early event in LSCC, increases B[a]P-induced human bronchial epithelial cell transformation, and might serve as a novel potential biomarker for early detection of LSCC.…”
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Evaluating Mental Health Policies for Middle School Students: Insights from Kunming City, Yunnan Province, China by Chunyu Li, Peerasit Kamnuansilpa, Xenia Ribaya Emperador-Garnace

“…Key influences on mental health include academic pressure, peer relationships, and family environment. A supportive setting built on trust, understanding, and recognition is essential for students’ well-being.   …”
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Examining the effect of underlying individual preferences for present over future on lung cancer screening participation: a cross-sectional analysis of a Korean National Cancer Scr... by Kui Son Choi, Yeol Kim, Jaeho Lee, Mina Suh, Seri Hong

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Fecal Keratin 8 Is a Noninvasive and Specific Marker for Intestinal Injury in Necrotizing Enterocolitis by Kewei Wang, Guozhong Tao, Zhen Sun, Jingjing Wei, Junlin Liu, Jordan Taylor, Michelle Gibson, Mirko Mostaghimi, Misty Good, Karl G. Sylvester

“…In conclusion, a modified ELISA protocol for the total K8 protein was successfully developed for the detection of fecal K8 in the clinical setting of premature newborns with NEC. …”
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From stroke to depression: The need for systematic screening for post-stroke depression by Mundih N. Njohjam, Swirri S. Nji, Ebsiy M. Nongse

“…Background: Post-stroke depression (PSD) negatively impacts the physical and mental well-being of stroke survivors. However, data on the prevalence and risk factors of PSD in African countries such as Cameroon are limited. …”
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”My AI is Lying to Me”: User-reported LLM hallucinations in AI mobile apps reviews by Rhodes Massenon, Ishaya Gambo, Javed Ali Khan, Christopher Agbonkhese, Ayed Alwadain

“…Using a mixed-methods approach, a heuristic-based User-Reported LLM Hallucination Detection algorithm were applied to identify  20,000 candidate reviews, from which 1,000 are manually annotated. …”
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