The impact of a participatory learning and action intervention on unmet need for contraception: a cluster-randomized controlled trial in rural Bihar, India by Mey-Ling Sommer, Lisa Bogler, S V Subramanian, Sebastian Vollmer

“…This work evaluates the impact of Gram Varta – a participatory learning and action intervention employed in women’s self-help groups in rural Bihar, India – on women’s contraceptive behavior and unmet need for contraception. …”
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Identification of M2 macrophage-related genes associated with diffuse large B-cell lymphoma via bioinformatics and machine learning approaches by Jiayi Zhang, Zhixiang Jia, Jiahui Zhang, Xiaohui Mu, Limei Ai

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Development and validation of novel machine learning-based prognostic models and propensity score matching for comparison of surgical approaches in mucinous breast cancer by Chunmei Chen, Jundong Wu, Yutong Fang, Yong Li, Qunchen Zhang

“…Cox regression analysis was conducted to identify independent prognostic factors. Ten machine learning algorithms were utilized to develop prognostic models, which were further validated using MBC patients from two Chinese hospitals. …”
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Application of Medical Images for Melanoma Detection Using a Multi‐Architecture Convolutional Neural Network From a Deep Learning Approach by Justice Williams Asare, Emmanuel Akwah Kyei, Seth Alornyo, Emmanuel Freeman, Martin Mabeifam Ujakpa, William Leslie Brown‐Acquaye, Alfred Coleman, Forgor Lempogo

“…ABSTRACT Melanoma has a higher tendency to spread to other parts of the human body swiftly if not detected and treated timely. This makes melanoma more dangerous than any other skin cancer disease. …”
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Supervised machine learning statistical models for visual outcome prediction in macular hole surgery: a single-surgeon, standardized surgery study by Kanika Godani, Vishma Prabhu, Priyanka Gandhi, Ayushi Choudhary, Shubham Darade, Rupal Kathare, Prathiba Hande, Ramesh Venkatesh

“…Abstract Purpose To evaluate the predictive accuracy of various machine learning (ML) statistical models in forecasting postoperative visual acuity (VA) outcomes following macular hole (MH) surgery using preoperative optical coherence tomography (OCT) parameters. …”
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Evaluating the impact of machine learning models on adult major depressive disorder using conventional treatment strategies: a systematic review approach by Nishant Yadav, Anamika Gulati, Varun Gulati, Prashant Yadav

“…Predicting treatment outcomes through machine learning (ML) models offers promise, potentially enabling more personalized and effective interventions. …”
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Histopathologic deep learning model for predicting tumor response to hepatic arterial infusion chemotherapy plus TKIs and ICIs in large hepatocellular carcinoma by Chunyu Lin, Yong Ren, Yu Huang, Shuqi Li, Jing Zhang, Shuai Kang, Shurong Li, Changxuan You, Qinghua Cao, Fang Liu

“…No significant differences in ORR were observed within the HTI group across different BCLC stages. A deep learning model, termed the Hepatocellular Carcinoma Artificial Intelligence Prediction Model (HAIM), was developed using pathological slides of HTI-treated patients (n = 194). …”
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Software educativo para el aprendizaje creativo del curso “Embriología comparada” / Educational Software for Creative Learning in the Comparative Embryology Course by Dedsy Francisca Villegas García

“…The outcomes demonstrated a high necessity of Comparative Embryology students to have educational software for creative learning, an electronic resource adapted to new communication and information technologies.…”
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Construction of a poor prognosis prediction and visualization system for intracranial aneurysm endovascular intervention treatment based on an improved machine learning model by Chunyu Lei, Anhui Fu, Bin Li, Shengfu Zhou, Jun Liu, Yu Cao, Bo Zhou

“…ObjectiveTo evaluate the clinical utility of improved machine learning models in predicting poor prognosis following endovascular intervention for intracranial aneurysms and to develop a corresponding visualization system.MethodsA total of 303 patients with intracranial aneurysms treated with endovascular intervention at four hospitals (FuShun County Zigong City People's Hospital, Nanchong Central Hospital, The Third People's Hospital of Yibin, The Sixth People's Hospital of Yibin) from January 2022 to September 2023 were selected. …”
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EcoTaskSched: a hybrid machine learning approach for energy-efficient task scheduling in IoT-based fog-cloud environments by Asfandyar Khan, Faizan Ullah, Dilawar Shah, Muhammad Haris Khan, Shujaat Ali, Muhammad Tahir

“…Before preprocessing the data was normalized, treated with feature engineering and augmentation, and then split into training and test sets. …”
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A deep machine learning model development for the biomarkers of the anatomical and functional anti-VEGF therapy outcome detection on retinal OCT images by B.E. Malyugin, S.N. Sakhnov, L.E. Axenova, K.D. Axenov, E.V. Kozina, V.V. Vronskaya, V.V. Myasnikova

“…We used a set of retrospective data in the form of 251 annotated OCT images obtained during the initial examination of patients who were treated with n-AMD using anti-VEGF therapy from 2014 to 2021 to develop a segmentation algorithm. …”
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An ensemble machine learning-based performance evaluation identifies top In-Silico pathogenicity prediction methods that best classify driver mutations in cancer by Subrata Das, Vatsal Patel, Shouvik Chakravarty, Arnab Ghosh, Anirban Mukhopadhyay, Nidhan K. Biswas

“…Missense somatic mutations in driver genes were treated as driver mutations, while non-driver mutations were randomly selected from other genes. …”
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Predicting distant metastasis of bladder cancer using multiple machine learning models: a study based on the SEER database with external validation by Xin Chang Zou, Xue Peng Rao, Jian Biao Huang, Jie Zhou, Hai Chao Chao, Tao Zeng

“…In addition, 118 patients treated at the Second Affiliated Hospital of Nanchang University were included as an external validation cohort. …”
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Correlation between Neutrophil-to-Lymphocyte Ratio and Diabetic Neuropathy in Chinese Adults with Type 2 Diabetes Mellitus Using Machine Learning Methods by Lijie Zhu, Yang Liu, Bingyan Zheng, Danmeng Dong, Xiaoyun Xie, Liumei Hu

“…We reviewed the medical records of 1154 diabetic patients treated at Tongji Hospital Affiliated to Tongji University from January 2022 to March 2023. …”
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Efficacy and prognostic factors of anti-VEGF treatment for neovascular age-related macular degeneration: An OCTA imaging-based deep learning analysis by Shengnan Liu, Yuanyuan Liu, Xiaohan Wu, Haochen Wang, Ziqi Jin, Peiru Wang, Jinyu Feng, Song Chen, Wei Zhou

“…Methods: We retrospectively analyzed data from patients treated with anti-VEGF at Tianjin Medical University General Hospital from August 2018 to August 2023, including 165 patients with exudative AMD. …”
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Electric Vehicle Energy Management Under Unknown Disturbances from Undefined Power Demand: Online Co-State Estimation via Reinforcement Learning by C. Treesatayapun, A. J. Munoz-Vazquez, S. K. Korkua, B. Srikarun, C. Pochaiya

“…In contrast to conventional reinforcement learning approaches, this method avoids the issue of high dimensionality and does not depend on extensive offline training. …”
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Changing practice in cystic fibrosis: Implementing objective medication adherence data at every consultation, a learning health system and quality improvement collaborative by Carla Girling, India Davids, Nikki Totton, Madelynne A. Arden, Daniel Hind, Martin J. Wildman

“…Method This was a mixed‐method study, treating each multidisciplinary team as an individual case. …”
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Effectiveness of a Machine Learning-Enabled Skincare Recommendation for Mild-to-Moderate Acne Vulgaris: 8-Week Evaluator-Blinded Randomized Controlled Trial by Misbah Noshela Ghazanfar, Ali Al-Mousawi, Christian Riemer, Benóný Þór Björnsson, Charlotte Boissard, Ivy Lee, Zarqa Ali, Simon Francis Thomsen

“…Therefore, personalized skincare recommendations may be beneficial for treating mild-to-moderate AV. ObjectiveThis study aimed to evaluate the effectiveness of a novel machine learning approach in predicting the optimal treatment for mild-to-moderate AV based on self-assessment and objective measures. …”
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Evolving Journal Policies for Ethical Use of Generative AI in Scientific Publishing by Afifa Ehsan, Ali Raza

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Physicians’ clinical experience and perspectives following a pilot, blended learning, point of care ultrasound course in Ghana- a mixed methods analysis by Anna Pathak, Felix Limbani, Yaw Asante Awuku, Angela Booth, Elizabeth Joekes

“…To expand POCUS expertise in Ghana, we co-developed and piloted a context specific, multi-disciplinary, blended learning programme, targeted at physicians of any grade or speciality providing acute care in the public health sector. …”
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