AIMC Topic: Clinical Trials, Phase II as Topic

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Allogenic faecal microbiota transplantation for antibiotic-associated diarrhoea in critically ill patients (FEBATRICE)-Study protocol for a multi-centre randomised controlled trial (phase II).

PloS one Dec 27, 2024
BACKGROUND: Exposure of critically ill patients to antibiotics lead to intestinal dysbiosis, which often manifests as antibiotic-associated diarrhoea. Faecal microbiota transplantation restores gut microbiota and may lead to faster resolution of diar...
Fecal Microbiota Transplantation Dysbiosis Clinical Trials, Phase II as Topic Multicenter Studies as Topic Randomized Controlled Trials as Topic Humans Female Anti-Bacterial Agents Male Prospective Studies Diarrhea Critical Illness Feces Gastrointestinal Microbiome
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Predicting Survival in Patients with Advanced NSCLC Treated with Atezolizumab Using Pre- and on-Treatment Prognostic Biomarkers.

Clinical pharmacology and therapeutics Jul 12, 2024
Existing survival prediction models rely only on baseline or tumor kinetics data and lack machine learning integration. We introduce a novel kinetics-machine learning (kML) model that integrates baseline markers, tumor kinetics, and four on-treatment...
Humans Machine Learning Prognosis Female Lung Neoplasms Antibodies, Monoclonal, Humanized Carcinoma, Non-Small-Cell Lung Clinical Trials, Phase II as Topic Clinical Trials, Phase III as Topic Aged Biomarkers, Tumor Male Middle Aged Immune Checkpoint Inhibitors
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Development of machine learning support for reading whole body diffusion-weighted MRI (WB-MRI) in myeloma for the detection and quantification of the extent of disease before and after treatment (MALIMAR): protocol for a cross-sectional diagnostic test accuracy study.

BMJ open Oct 5, 2022
INTRODUCTION: Whole-body MRI (WB-MRI) is recommended by the National Institute of Clinical Excellence as the first-line imaging tool for diagnosis of multiple myeloma. Reporting WB-MRI scans requires expertise to interpret and can be challenging for ...
Whole Body Imaging Diagnostic Tests, Routine Humans Multiple Myeloma Retrospective Studies Machine Learning Clinical Trials, Phase III as Topic Cross-Sectional Studies Chlorobenzenes Magnetic Resonance Imaging Clinical Trials, Phase II as Topic Sulfides
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Application of machine learning to predict reduction in total PANSS score and enrich enrollment in schizophrenia clinical trials.

Clinical and translational science May 3, 2021
Clinical trial efficiency, defined as facilitating patient enrollment, and reducing the time to reach safety and efficacy decision points, is a critical driving factor for making improvements in therapeutic development. The present work evaluated a m...
Humans Machine Learning Female Aged Young Adult Antipsychotic Agents Proof of Concept Study Treatment Outcome Clinical Trials, Phase II as Topic Patient Selection Adult Schizophrenia Male Datasets as Topic Middle Aged Adolescent
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Deep learning-based classification and segmentation of retinal cavitations on optical coherence tomography images of macular telangiectasia type 2.

The British journal of ophthalmology Nov 23, 2020
AIM: To develop a fully automatic algorithm to segment retinal cavitations on optical coherence tomography (OCT) images of macular telangiectasia type 2 (MacTel2).
Humans Deep Learning Multicenter Studies as Topic Clinical Trials, Phase II as Topic Tomography, Optical Coherence Retina Retinal Telangiectasis
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A CNN-aided method to predict glaucoma progression using DARC (Detection of Apoptosing Retinal Cells).

Expert review of molecular diagnostics May 3, 2020
BACKGROUND: A key objective in glaucoma is to identify those at risk of rapid progression and blindness. Recently, a novel first-in-man method for visualising apoptotic retinal cells called DARC (Detection-of-Apoptosing-Retinal-Cells) was reported. T...
Automation Annexin A5 Clinical Trials, Phase II as Topic Tomography, Optical Coherence Observer Variation Retinal Ganglion Cells Algorithms Female Aged Adult Male Middle Aged Disease Progression Image Processing, Computer-Assisted Apoptosis Humans Neural Networks, Computer Glaucoma
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Identification of Non-Small Cell Lung Cancer Sensitive to Systemic Cancer Therapies Using Radiomics.

Clinical cancer research : an official journal of the American Association for Cancer Research Mar 20, 2020
PURPOSE: Using standard-of-care CT images obtained from patients with a diagnosis of non-small cell lung cancer (NSCLC), we defined radiomics signatures predicting the sensitivity of tumors to nivolumab, docetaxel, and gefitinib.
Clinical Trials, Phase III as Topic Gefitinib Randomized Controlled Trials as Topic Clinical Trials, Phase II as Topic Nivolumab Docetaxel Retrospective Studies Tomography, X-Ray Computed Female Survival Rate Male Disease Progression Lung Neoplasms Antineoplastic Combined Chemotherapy Protocols Carcinoma, Non-Small-Cell Lung Humans Machine Learning Prognosis
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On strategic choices faced by large pharmaceutical laboratories and their effect on innovation risk under fuzzy conditions.

Artificial intelligence in medicine Aug 11, 2019
OBJECTIVES: We develop a fuzzy evaluation model that provides managers at different responsibility levels in pharmaceutical laboratories with a rich picture of their innovation risk as well as that of competitors. This would help them take better str...
Humans Research Risk Assessment Fuzzy Logic Models, Statistical Clinical Trials, Phase II as Topic Probability Drug Industry Inventions Decision Making, Organizational Drug Approval Strategic Planning Clinical Trials, Phase III as Topic Clinical Trials, Phase I as Topic Clinical Trials, Phase IV as Topic
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Automated quantitative tumour response assessment of MRI in neuro-oncology with artificial neural networks: a multicentre, retrospective study.

The Lancet. Oncology Apr 2, 2019
BACKGROUND: The Response Assessment in Neuro-Oncology (RANO) criteria and requirements for a uniform protocol have been introduced to standardise assessment of MRI scans in both clinical trials and clinical practice. However, these criteria mainly re...
Tumor Burden Humans Image Interpretation, Computer-Assisted Automation Neural Networks, Computer Germany Diagnosis, Computer-Assisted Databases, Factual Clinical Trials, Phase III as Topic Time Factors Retrospective Studies Reproducibility of Results Randomized Controlled Trials as Topic Treatment Outcome Female Brain Neoplasms Clinical Trials, Phase II as Topic Magnetic Resonance Imaging Male Predictive Value of Tests Multicenter Studies as Topic Disease Progression Workflow
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A Tool for Predicting Regulatory Approval After Phase II Testing of New Oncology Compounds.

Clinical pharmacology and therapeutics Sep 24, 2015
We developed an algorithm (ANDI) for predicting regulatory marketing approval for new cancer drugs after phase II testing has been conducted, with the objective of providing a tool to improve drug portfolio decision-making. We examined 98 oncology dr...
Neoplasms Antineoplastic Agents Clinical Trials, Phase II as Topic Drug Approval Humans Machine Learning Algorithms Forecasting
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