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Treatment prediction
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The process of neural stem cell (NSC) differentiation into neurons is crucial for the development of potential cell-centered treatments for central nervous system disorders. However, predicting, identifying, and anticipating this differentiation is complex. In this study, we propose the implementation of a convolutional neural network model for the predictable recognition of NSC fate, utilizing single-cell brightfield images.
7p
vithomson
02-07-2024
0
0
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Part 2 of ebook "Machine learning in medicine - A complete overview" provides readers with contents including: Chapter 50 - Neural networks for assessing relationships that are typically nonlinear; Chapter 51 - Complex samples methodologies for unbiased sampling; Chapter 52 - Correspondence analysis for identifying the best of multiple treatments in multiple groups; Chapter 53 - Decision trees for decision analysis; Chapter 54 - Multi-dimensional scaling for visualizing experienced drug efficacies; Chapter 55 - Stochastic processes for long term predictions from short term observations;...
194p
daonhiennhien
03-07-2024
1
1
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Immunotherapy based on the application of immune checkpoint inhibitors (ICIs) is one of the standard treatments for advanced non-small cell lung cancer (NSCLC). Non-alcoholic fatty liver Disease (NAFLD) has demonstrated predictive value for response to immunotherapy in non-lung cancer types.
10p
vishanshan
27-06-2024
2
1
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Accurate assessment of axillary status after neoadjuvant therapy for breast cancer patients with axil‑ lary lymph node metastasis is important for the selection of appropriate subsequent axillary treatment decisions. Our objectives were to accurately predict whether the breast cancer patients with axillary lymph node metastases could achieve axillary pathological complete response (pCR).
13p
vishanshan
27-06-2024
2
1
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Ferroptosis has important value in cancer treatment. It is signifcant to explore the new ferroptosis-related lncRNAs prediction model in Hepatocellular carcinoma (HCC) and the potential molecular mechanism of ferroptosis-related lncRNAs.
15p
vishanshan
27-06-2024
1
1
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To explore the value of six machine learning models based on PET/CT radiomics combined with EGFR in predicting brain metastases of lung adenocarcinoma. Retrospectively collected 204 patients with lung adenocarcinoma who underwent PET/CT examination and EGFR gene detection before treatment from Cancer Hospital Affiliated to Shandong First Medical University in 2020.
13p
vishanshan
27-06-2024
2
1
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Although papillary thyroid cancer (PTC) patients are known to have an excellent prognosis, up to 30% of patients experience disease recurrence after initial treatment. Accurately predicting disease prognosis remains a challenge given that the predictive value of several predictors remains controversial.
12p
vishanshan
27-06-2024
2
1
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Clear cell carcinoma of the kidney is a common urological malignancy characterized by poor patient prognosis and treatment outcomes. Modulation of vasculogenic mimicry in tumor cells alters the tumor microenvironment and the influx of tumor-infiltrating lymphocytes, and the combination of its inducers and immune checkpoint inhibitors plays a synergistic role in enhancing antitumor effects.
16p
vishanshan
27-06-2024
1
1
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Predicting short-term efficacy and intracranial progression-free survival (iPFS) in epidermal growth factor receptor gene mutated (EGFR-mutated) lung adenocarcinoma patients with brain metastases who receive third-generation epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) therapy was of great significance for individualized treatment.
15p
vishanshan
27-06-2024
1
1
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Chemoradiotherapy is a critical treatment for patients with locally advanced and unresectable nonsmall cell lung cancer (NSCLC), and it is essential to identify high-risk patients as early as possible owing to the high incidence of radiation pneumonitis (RP). This study aimed to investigate the value of computed tomography (CT)-based radiomics combined with genomics in analyzing the risk of grade≥2 RP in unresectable stage III NSCLC.
10p
vishanshan
27-06-2024
1
1
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This research designeded to: 1. Analyze the efficacy and safety of Palbociclib treatment in HR-positive and HER2-negative (HR+/HER2-) metastatic breast cancer(MBC) patients. 2. Establish and validate a nomogram model for predicting the progression-free survival (PFS) rates of 6 months, 12 months, and 18 months in HR+/HER2- MBC patients after receiving Palbociclib plus endocrine therapy (ET).
13p
vishanshan
27-06-2024
2
1
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Depression is prevalent among Operation Enduring Freedom and Operation Iraqi Freedom (OEF/ OIF) Veterans, yet rates of Veteran mental health care utilization remain modest. The current study examined: factors in electronic health records (EHR) associated with lack of treatment initiation and treatment delay; the accuracy of regression and machine learning models to predict initiation of treatment.
10p
vishanshan
27-06-2024
3
1
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This study aims to develop a nomogram integrating inflammation (NLR), Prognostic Nutritional Index (PNI), and EBV DNA (tumor burden) to achieve personalized treatment and prediction for stage IVA NPC. Furthermore, it endeavors to pinpoint specific subgroups that may derive significant benefits from S-1 adjuvant chemotherapy.
16p
vishanshan
27-06-2024
1
1
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In oral squamous cell carcinoma (OSCC), the tumor-node-metastasis (TNM) staging system is a significant factor that influences prognosis and treatment decisions for OSCC patients. Unfortunately, TNM staging does not consistently predict patient prognosis and patients with identical clinicopathological characteristics may have vastly diferent survival outcomes.
21p
vikoch
27-06-2024
1
1
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The axillary lymph-node metastatic burden is closely associated with treatment decisions and prognosis in breast cancer patients. This study aimed to explore the value of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT)–based radiomics in combination with ultrasound and clinical pathological features for predicting axillary lymph-node metastatic burden in breast cancer.
14p
vikoch
27-06-2024
1
1
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This study is based on network pharmacology and molecular docking technology to predict the possible target of PSP treatment of breast cancer, and use experiments to verify the effect and mechanism of PSP on breast cancer.
14p
vikoch
27-06-2024
1
1
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Despite recent improvements in cancer detection and survival rates, managing cancer-related pain remains a significant challenge. The objective of this work was to select a panel of biomarkers of central pain processing and modulation and assess their ability to predict chronic pain in patients with cancer using predictive artificial intelligence (AI) algorithms.
11p
vikoch
27-06-2024
1
1
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Multicenter non-small cell lung cancer (NSCLC) patient data is information-rich. However, its direct integration becomes exceptionally challenging due to constraints involving different healthcare organizations and regulations.
11p
vikoch
27-06-2024
2
1
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Although radical surgical resection is the most effective treatment for hepatocellular carcinoma (HCC), the high rate of postoperative recurrence remains a major challenge, especially in patients with alpha-fetoprotein (AFP)-negative HCC who lack effective biomarkers for postoperative recurrence surveillance. In this study, we propose to develop a radiomics model based on preoperative CECT to predict the risk of early recurrence after surgery in AFP-negative HCC.
12p
vikoch
27-06-2024
1
1
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Preoperative prediction of International Federation of Gynecology and Obstetrics (FIGO) stage in patients with epithelial ovarian cancer (EOC) is crucial for determining appropriate treatment strategy. This study aimed to explore the value of contrast-enhanced CT (CECT) radiomics in predicting preoperative FIGO staging of EOC, and to validate the stability of the model through an independent external dataset.
11p
vikoch
27-06-2024
1
1
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