Psychometric properties of instruments for assessing adherence to oral antineoplastic agents: a COSMIN systematic review by Miaomiao Sun, Kanghui Huang, Suxiang Liu, Chuchu Fang, Lili Yang

“…None of the studies explored measurement error, cross-cultural validity/measurement invariance, and responsiveness of the instruments. …”
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Effectiveness of sensorimotor training on pain, cervical joint position sense, range of motion, balance, and disability in chronic neck pain: A systematic review by Sahar Zaidi, Sohrab Ahmad Khan, Saima Zaki, Habiba Sundus, Md Farhan Alam, Shibili Nuhmani

“…Long-term improvements included enhanced postural stability, reduced joint position error, and decreased disability. Methodological quality of included studies was moderate to high, with several studies achieving long-term outcome sustainability. …”
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Psychometric properties of screening tools for mild cognitive impairment in older adults based on COSMIN guidelines: a systematic review by Shasha Wen, Dongmei Cheng, Nana Zhao, Xinyu Chen, Xianying Lu, Yue Li, Huanle Liu, Jing Gao, Chaoming Hou, Ran Xu

“…No data were found on cross-cultural validity/measurement invariance, measurement error, or responsiveness. The final three instruments, AV-MoCA, HKBC, and Qmci-G, received class A recommendations and were recommended for use. …”
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Domain knowledge-infused pre-trained deep learning models for efficient white blood cell classification by P. Jeneessha, Vinoth Kumar Balasubramanian

“…Computer-aided diagnosis (CAD) reduces manual intervention, avoids errors, speeds up medical analysis, and provides accurate medical reports. …”
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CerviXpert: A multi-structural convolutional neural network for predicting cervix type and cervical cell abnormalities by Rashik Shahriar Akash, Radiful Islam, SM Saiful Islam Badhon, KSM Tozammel Hossain

“…Traditional diagnostic methods like Pap smears and cervical biopsies rely heavily on the skills of cytologists, making the process prone to errors. This study aims to develop CerviXpert, a multi-structural convolutional neural network designed to classify cervix types and detect cervical cell abnormalities efficiently. …”
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Nurses' occupational fatigue level and risk factors: A systematic review and meta-analysis. by Rong Pi, Yunfang Liu, Rong Yan, Zong De, Yali Wan, Yi Chen, Zihan He, Fang Liu, Yan Wang, Suyun Li

“…Studies have consistently linked occupational fatigue to decreased productivity, heightened error rates, and compromised decision-making abilities, posing significant risks to both individual nurses and healthcare organizations. …”
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Relationship between Tai Chi and clinical outcomes in elderly patients with COVID-19: a protocol for systematic review and dose–response meta-analysis by Yang Wang, Na Li, Xiao Peng, Chun Wang, Sheng He, Jinfeng Yang, Yuanpeng Liao

“…Two independent reviewers will select the studies, extract the data, and analyse them on EndNote V.X9.0 and Stata V.12.1. The robust error meta-regression model will be used to establish the dose–response relationships between Tai Chi and clinical outcomes. …”
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FruitsMultiNet: A deep neural network approach to identify fruits through multi-scale feature fusion using mobile interface by Tasauf Mim, Md Mahbubur Rahman, Jahanur Biswas, Ahmad Shafkat, Khandaker Mohammad Mohi Uddin

“…A reliable fruit classification system during harvest and post-harvest phases can minimize time, cost, and human error while modernizing the processes of sorting, labeling, and packaging. …”
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Risk factors for fear of falling in stroke patients: a systematic review and meta-analysis by Li Ma, Qi Xie, Juhong Pei, Ling Gou, Yabin Zhang, Juanping Zhong, Yujie Su, Xinglei Wang, Xinman Dou

“…Measurement of heterogeneity between studies was high for all outcomes (I2=0%–93%), indicating that the substantial interstudy heterogeneity in estimated proportions was not attributed to the sampling error. Sensitivity analysis (leave-one-out method) showed that the pooled estimate was stable.Conclusion This meta-analysis indicated that female population, impaired balance ability, lower mobility, history of falls and walking aid in patients with stroke might be at greater risk for FoF. …”
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COMMUNICATING THE SEVERE DIAGNOSIS – PSYCHOLOGICAL, ETHICAL AND LEGAL ASPECTS by Andrada PÂRVU, Adina REBELEANU, Anca BOJAN

“…The doctors questioned as part of a study reveal that they‘ve learned to communicate a severe diagnosis by trial and error. This being said we recommend the inception of practical doctor-patient communication courses that could lead to improving doctor-patient relationships, communication of the diagnosis being their foundations. …”
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Machine learning models predicting risk of revision or secondary knee injury after anterior cruciate ligament reconstruction demonstrate variable discriminatory and accuracy perfor... by Benjamin Blackman, Prushoth Vivekanantha, Rafay Mughal, Ayoosh Pareek, Anthony Bozzo, Kristian Samuelsson, Darren de SA

“…Four studies reported calibration error, with all four studies demonstrating significant miscalibration at either two or five-year follow-ups amongst 10 of 14 models assessed. …”
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Segmentation of ADPKD Computed Tomography Images with Deep Learning Approach for Predicting Total Kidney Volume by Ting-Wen Sheng, Djeane Debora Onthoni, Pushpanjali Gupta, Tsong-Hai Lee, Prasan Kumar Sahoo

“…However, manual localization and segmentation are tedious, time-consuming tasks and are prone to human error. Specifically, there is a lack of studies that focus on CT modality variation. …”
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GenVFNet: Generating Visual Field From Optical Coherence Tomography Angiography by Conditional Generative Adversarial Networks by Anita Manassakorn, Supatana Auethavekiat, Vera Sa-Ing, Sunee Chansangpetch, Kitiya Ratanawongphaibul, Nopphawan Uramphorn, Visanee Tantisevi

“…In the experiment, GenRawVFs were compared with actual pattern deviation images (RealRawVF) using the structural similarity index measure (SSIM), normalized root mean square error (NRMSE), Fréchet inception distance (FID), and confusion matrix. …”
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Bangladeshi Vehicle Classification and Detection Using Deep Convolutional Neural Networks With Transfer Learning by Farid, Proshanta Kumer Das, Monirul Islam, Ebna Sina

“…The proposed system can detect and classify low-speed and high-speed vehicles with an average 93% detection rate and 98% accuracy, while facing challenges that include issues with image annotation tools like poor label visibility, lack of error checking, and limited guidance, as well as difficulties in setting up the NVIDIA Jetson Nano embedded device for efficient model deployment.…”
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Enzyme replacement therapy for Anderson-Fabry disease: A complementary overview of a Cochrane publication through a linear regression and a pooled analysis of proportions from coho... by Regina El Dib, Huda Gomaa, Alberto Ortiz, Juan Politei, Anil Kapoor, Fellype Barreto

“…<h4>Background</h4>Anderson-Fabry disease (AFD) is an X-linked recessive inborn error of glycosphingolipid metabolism caused by a deficiency of alpha-galactosidase A. …”
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Deep learning-based dual optimization framework for accurate thyroid disease diagnosis using CNN architectures by Zeeshan Ali Haider, Nasser A Alsadhan, Fida Muhammad Khan, Waleed Al-Azzawi, Inam Ullah Khan, Inam Ullah

“…Traditional diagnostic approaches, reliant on manual interpretation of medical images, are time-consuming and prone to errors. This study introduces a novel deep learning framework utilizing advanced Convolutional Neural Networks (CNNs), specifically modified ResNet and InceptionV3 architectures, to improve the accuracy and efficiency of thyroid disease diagnosis. …”
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Enhanced Panoramic Radiograph-Based Tooth Segmentation and Identification Using an Attention Gate-Based Encoder–Decoder Network by Salih Taha Alperen Özçelik, Hüseyin Üzen, Abdulkadir Şengür, Hüseyin Fırat, Muammer Türkoğlu, Adalet Çelebi, Sema Gül, Nebras M. Sobahi

“…Precise dental disease segmentation requires reliable tooth numbering, which may be prone to errors if performed manually. These steps can be automated using artificial intelligence, which may provide fast and accurate results. …”
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Investigation of ensembles of deep learning models for improved chronic kidney diseases detection in CT scan images by I.I. Ayogu, C.F. Daniel, B.A. Ayogu, J.N. Odii, C.L. Okpalla, E.C. Nwokorie

“…Thereafter, two ensemble configurations – Inception-v3-CCT-SwinT and VGG16-EANet-ResNet50 - were studied. …”
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Migrating mistakes of the publication history of the magazine „Moteris" by Genovaitė Burneikienė

“…As a result, facts without authentic verification are sometimes published, leading to errors that propagate in periodicals and scientific works. …”
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Synergistic AI-resident approach achieves superior diagnostic accuracy in tertiary ophthalmic care for glaucoma and retinal disease by Dalia Camacho-García-Formentí, Gabriela Baylón-Vázquez, Karen Arriozola-Rodríguez, Enrique Avalos-Ramirez, Curt Hartleben-Matkin, Hugo Valdez-Flores, Damaris Hodelin-Fuentes, Alejandro Noriega

“…AI’s CDR estimates showed lower mean absolute error (0.056 vs. 0.105, p &lt; 0.001) and higher correlation with expert measurements (r = 0.728 vs. r = 0.538). …”
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