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Journal of Cellular and Molecular... Mar 2024Deep learning is gaining importance due to its wide range of applications. Many researchers have utilized deep learning (DL) models for the automated diagnosis of cancer...
Deep learning is gaining importance due to its wide range of applications. Many researchers have utilized deep learning (DL) models for the automated diagnosis of cancer patients. This paper provides a systematic review of DL models for automated diagnosis of cancer patients. Initially, various DL models for cancer diagnosis are presented. Five major categories of cancers such as breast, lung, liver, brain and cervical cancer are considered. As these categories of cancers have a very high percentage of occurrences with high mortality rate. The comparative analysis of different types of DL models is drawn for the diagnosis of cancer at early stages by considering the latest research articles from 2016 to 2022. After comprehensive comparative analysis, it is found that most of the researchers achieved appreciable accuracy with implementation of the convolutional neural network model. These utilized the pretrained models for automated diagnosis of cancer patients. Various shortcomings with the existing DL-based automated cancer diagnosis models are also been presented. Finally, future directions are discussed to facilitate further research for automated diagnosis of cancer patients.
Topics: Humans; Deep Learning; Lung; Neural Networks, Computer; Tomography, X-Ray Computed; Neoplasms; Diagnosis, Computer-Assisted
PubMed: 38426930
DOI: 10.1111/jcmm.18144 -
Genes Feb 2024Mutations in the gene are a common cause of severe or even lethal nemaline myopathy. Some cases with mild forms have been described, although the cases are still... (Review)
Review
BACKGROUND
Mutations in the gene are a common cause of severe or even lethal nemaline myopathy. Some cases with mild forms have been described, although the cases are still anecdotal. The aim of this paper was to systematically review the cases described in the literature and to describe a 12-year clinical and imaging follow-up in an Italian patient with KLHL40- related myopathy in order to suggest possible follow-up measurements.
METHODS
Having searched through three electronic databases (PubMed, Scopus, and EBSCO), 18 articles describing 65 patients with homozygous or compound heterozygous mutations were selected. A patient with a homozygous mutation (c.1582G>A/p.E528K) was added and clinical and genetic data were collected.
RESULTS
The most common mutation identified in our systematic review was the (c.1516A>C) followed by the (c.1582G>A). In our review, 60% percent of the patients died within the first 4 years of life. Clinical features were similar across the sample. Unfortunately, however, there is no record of the natural history data in the surviving patients. The 12-year follow-up of our patient revealed a slow improvement in her clinical course, identifying muscle MRI as the only possible marker of disease progression.
CONCLUSIONS
Due to its clinical and genotype homogeneity, KLHL40-related myopathy may be a condition that would greatly benefit from the development of new gene therapies; muscle MRI could be a good biomarker to monitor disease progression.
Topics: Humans; Female; Muscle, Skeletal; Follow-Up Studies; Muscle Proteins; Myopathies, Nemaline; Biomarkers; Disease Progression
PubMed: 38397198
DOI: 10.3390/genes15020208 -
Diagnostics (Basel, Switzerland) Feb 2024Anemia is the main extraintestinal comorbidity of Inflammatory Bowel Disease (IBD). Differentiating the type of anemia in these disorders is still a challenge. Hepcidin... (Review)
Review
BACKGROUND
Anemia is the main extraintestinal comorbidity of Inflammatory Bowel Disease (IBD). Differentiating the type of anemia in these disorders is still a challenge. Hepcidin could be a promising biomarker to identify iron deficiency anemia (IDA), anemia of chronic disease (ACD) and the concomitant presence of both IDA and ACD.
METHODS
To evaluate the potential role of hepcidin dosage in the management of anemia in IBD patients, we performed a systematic review by a comprehensive literature analysis of original papers reporting the dosage of hepcidin in IBD patients. In all the articles reviewed, the dosage of ferritin was reported, and the correlation between hepcidin and ferritin has been used to compare these two biomarkers.
RESULTS
A total of 12 articles concerning the dosage of hepcidin in IBD were included, comprising in total of 976 patients. The results of the hepcidin values in IBD patients when compared with controls were conflicting. In fact, four articles described an increase in this biomarker, three showed a decrease and five did not find significant differences. The correlation with ferritin was positive and significant. In three studies, some differences between hepcidin dosages and ferritin levels indicate a possible role when IDA and ACD could be present at the same time.
CONCLUSIONS
Considering the contradictory data of the studies, the diagnostic role of hepcidin as a biomarker remains elusive in IBD patients. These differences could be due to the clinical characteristics of the patients enrolled that should be better defined in the future. A suitable clinical trial should be designed to outline the possible role of hepcidin in differentiating IDA, ACD and concomitant IDA and ACD in IBD patients. At the moment, ferritin still remains the best marker to diagnose these conditions, in addition to hemoglobin, transferrin saturation and CRP as recommended by the ECCO guidelines.
PubMed: 38396414
DOI: 10.3390/diagnostics14040375 -
Neurology(R) Neuroimmunology &... May 2024Susac syndrome (SuS) is an orphan microangiopathic disease characterized by a triad of encephalopathy, visual disturbances due to branch retinal artery occlusions, and... (Review)
Review
Susac syndrome (SuS) is an orphan microangiopathic disease characterized by a triad of encephalopathy, visual disturbances due to branch retinal artery occlusions, and sensorineuronal hearing loss. Our previous systematic review on all cases of SuS reported until 2012 allowed for a better understanding of clinical presentation and diagnostic findings. Based on these data, we suggested diagnostic criteria in 2016 to allow early diagnosis and treatment of SuS. In view of the accumulation of new SuS cases reported in the last 10 years and improved diagnostic tools, we here aimed at updating the demographic and clinical features of SuS and to review the updated ancillary tests being used for SuS diagnosis. Therefore, based on the 2016 criteria, we systematically collected and evaluated data on SuS published from January 2013 to March 2022.
Topics: Humans; Susac Syndrome; Magnetic Resonance Imaging; Brain Diseases; Vision Disorders; Diagnosis, Differential
PubMed: 38364193
DOI: 10.1212/NXI.0000000000200209 -
Medicine Feb 2024Deep learning techniques explain the enormous potential of medical image analysis, particularly in digital pathology. Concurrently, molecular markers have gained...
BACKGROUND
Deep learning techniques explain the enormous potential of medical image analysis, particularly in digital pathology. Concurrently, molecular markers have gained increasing significance over the past decade in the context of glioma patients, providing novel insights into diagnosis and more personalized treatment options. Deep learning combined with imaging and molecular analysis enables more accurate prognostication of patients, more accurate treatment plan proposals, and accurate biomarker (IDH) prediction for gliomas. This systematic study examines the development of deep learning techniques for IDH prediction using histopathology images, spanning the period from 2019 to 2023.
METHOD
The study adhered to the PRISMA reporting requirements, and databases including PubMed, Google Scholar, Google Search, and preprint repositories (such as arXiv) were systematically queried for pertinent literature spanning the period from 2019 to the 30th of 2023. Search phrases related to deep learning, digital pathology, glioma, and IDH were collaboratively utilized.
RESULTS
Fifteen papers meeting the inclusion criteria were included in the analysis. These criteria specifically encompassed studies utilizing deep learning for the analysis of hematoxylin and eosin images to determine the IDH status in patients with gliomas.
CONCLUSIONS
When predicting the status of IDH, the classifier built on digital pathological images demonstrates exceptional performance. The study's predictive effectiveness is enhanced with the utilization of the appropriate deep learning model. However, external verification is necessary to showcase their resilience and universality. Larger sample sizes and multicenter samples are necessary for more comprehensive research to evaluate performance and confirm clinical advantages.
Topics: Humans; Brain Neoplasms; Deep Learning; Glioma; Biomarkers; Isocitrate Dehydrogenase; Mutation; Magnetic Resonance Imaging; Multicenter Studies as Topic
PubMed: 38363910
DOI: 10.1097/MD.0000000000037150 -
Frontiers in Oncology 2024This study aimed to evaluate the value of F-FDG PET/CT radiomics in predicting EGFR gene mutations in non-small cell lung cancer by meta-analysis.
OBJECTIVE
This study aimed to evaluate the value of F-FDG PET/CT radiomics in predicting EGFR gene mutations in non-small cell lung cancer by meta-analysis.
METHODS
The PubMed, Embase, Cochrane Library, Web of Science, and CNKI databases were searched from the earliest available date to June 30, 2023. The meta-analysis was performed using the Stata 15.0 software. The methodological quality and risk of bias of included studies were assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 and Radiomics Quality Score criteria. The possible causes of heterogeneity were analyzed by meta-regression.
RESULTS
A total of 17 studies involving 3763 non-small cell lung cancer patients were finally included. We analyzed 17 training cohorts and 10 validation cohorts independently. Within the training cohort, the application of F-FDG PET/CT radiomics in predicting EGFR mutations in NSCLC demonstrated a sensitivity of 0.76 (95% CI: 0.70-0.81) and a specificity of 0.78 (95% CI: 0.74-0.82), accompanied by a positive likelihood ratio of 3.5 (95% CI:3.0-4.2), a negative likelihood ratio of 0.31 (95% CI: 0.24-0.39), a diagnostic odds ratio of 11.0 (95% CI: 8.0-16.0), and an area under the curve (AUC) of 0.84 (95% CI: 0.80-0.87). In the validation cohort, the values included a sensitivity of 0.76 (95% CI: 0.67-0.83), a specificity of 0.75 (95% CI: 0.68-0.80), a positive likelihood ratio of 3.0 (95% CI:2.4-3.8), a negative likelihood ratio of 0.32 (95% CI: 0.24-0.44), a diagnostic odds ratio of 9 (95% CI: 6-15), and an AUC of 0.82 (95% CI: 0.78-0.85). The average Radiomics Quality Score (RQS) across studies was 10.47 ± 4.72. Meta-regression analysis identifies the application of deep learning and regions as sources of heterogeneity.
CONCLUSION
F-FDG PET/CT radiomics may be useful in predicting mutation status of the EGFR gene in non-small cell lung cancer.
SYSTEMATIC REVIEW REGISTRATION
https://www.crd.york.ac.uk/PROSPERO, identifier CRD42022385364.
PubMed: 38361781
DOI: 10.3389/fonc.2024.1281572 -
Journal of Biomedical Physics &... Feb 2024Based on the Liver Imaging Data and Reporting System (LI-RADS) guidelines, Hepatocellular Carcinoma (HCC) can be diagnosed using imaging criteria in patients at risk of... (Review)
Review
Evidence Supporting Diagnostic Value of Liver Imaging Reporting and Data System for CT- and MR Imaging-based Diagnosis of Hepatocellular Carcinoma: A Systematic Review and Meta-analysis.
BACKGROUND
Based on the Liver Imaging Data and Reporting System (LI-RADS) guidelines, Hepatocellular Carcinoma (HCC) can be diagnosed using imaging criteria in patients at risk of HCC.
OBJECTIVE
This study aimed to assess the diagnostic value of LI-RADS in high-risk patients with HCC.
MATERIAL AND METHODS
This systematic review is conducted on international databases, including Google Scholar, Web of Science, PubMed, Embase, PROQUEST, and Cochrane Library, with appropriate keywords. Using the binomial distribution formula, the variance of each study was calculated, and all the data were analyzed using STATA version 16. The pooled sensitivity and specificity were determined using a random-effects meta-analysis approach. Also, we used the chi-squared test and I index to calculate heterogeneity among studies, and Funnel plots and Egger tests were used for evaluating publication bias.
RESULTS
The pooled sensitivity was estimated at 0.80 (95% CI 0.76-0.84). According to different types of Liver Imaging Reporting and Data Systems (LI-RADS), the highest pooled sensitivity was in version 2018 (0.83 (95% CI 0.79-0.87) (I: 80.6%, of chi 2 test for heterogeneity <0.001 and T: 0.001). The pooled specificity was estimated as 0.89 (95% CI 0.87-0.92). According to different types of LI-RADS, the highest pooled specificity was in version 2014 (93.0 (95% CI 89.0-96.0) (I: 81.7%, of chi 2 test for heterogeneity <0.001 and T: 0.001).
CONCLUSION
LI-RADS can assist radiologists in achieving the required sensitivity and specificity in high-risk patients suspected to have HCC. Therefore, this strategy can serve as an appropriate tool for identifying HCC.
PubMed: 38357604
DOI: 10.31661/jbpe.v0i0.2211-1562 -
Asian Journal of Psychiatry Mar 2024Yoga is gradually being explored as a potential complementary intervention in addition to psychiatric drugs for schizophrenia. However, there are conflicts on the... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Yoga is gradually being explored as a potential complementary intervention in addition to psychiatric drugs for schizophrenia. However, there are conflicts on the efficacy of yoga for schizophrenia. This meta-analysis was aimed to evaluate the association of yoga intervention with reductions on clinical symptoms and improvements in quality of life (QoL) as well as social functioning among schizophrenia.
METHOD
Systematic literature search was undertaken to identify all RCTs that compared yoga with active or passive controls for patients with schizophrenia from inception to July 2023. The outcomes were measurements of positive symptoms, negative symptoms, QoL and social functioning. Random-effects models were performed to calculate the effect sizes in the standardized mean differences reporting as Hedges' s g statistic.
RESULTS
19 studies enrolling 1274 participants with schizophrenia were included. Yoga had a medium effect on positive symptoms in the short term (Hedges's g = 0.31) and small effect in the long term (Hedges's g = 0.18). Medium significant effects were also found on negative symptoms in both the short term (Hedges's g = 0.44) and the long term (Hedges's g = 0.35). Yoga had a significant impact on improving both total QoL (Hedges's g = 0.34) and social functioning (Hedges's g = 0.45) with medium effect sizes.
CONCLUSIONS
Yoga was associated with significant reductions on negative and positive symptoms, and significant improvements in QoL as well as social functioning in patients with schizophrenia. Future research should explore the long-term efficacy of yoga for schizophrenia, encompassing more diverse populations.
Topics: Humans; Quality of Life; Schizophrenia; Social Interaction; Yoga
PubMed: 38342034
DOI: 10.1016/j.ajp.2024.103959 -
Cells Feb 2024Glycogen metabolism is a form of crucial metabolic reprogramming in cells. PYGB, the brain-type glycogen phosphorylase (GP), serves as the rate-limiting enzyme of... (Review)
Review
Glycogen metabolism is a form of crucial metabolic reprogramming in cells. PYGB, the brain-type glycogen phosphorylase (GP), serves as the rate-limiting enzyme of glycogen catabolism. Evidence is mounting for the association of PYGB with diverse human diseases. This review covers the advancements in PYGB research across a range of diseases, including cancer, cardiovascular diseases, metabolic diseases, nervous system diseases, and other diseases, providing a succinct overview of how PYGB functions as a critical factor in both physiological and pathological processes. We present the latest progress in PYGB in the diagnosis and treatment of various diseases and discuss the current limitations and future prospects of this novel and promising target.
Topics: Humans; Glycogen Phosphorylase; Glycogen; Brain
PubMed: 38334681
DOI: 10.3390/cells13030289 -
Cureus Jan 2024This systematic review examines the transformative impact of artificial intelligence (AI) in managing lung disorders through a comprehensive analysis of articles... (Review)
Review
This systematic review examines the transformative impact of artificial intelligence (AI) in managing lung disorders through a comprehensive analysis of articles spanning 2014 to 2023. Evaluating AI's multifaceted roles in radiological imaging, disease burden prediction, detection, diagnosis, and molecular mechanisms, this review presents a critical synthesis of key insights from select articles. The findings underscore AI's significant strides in bolstering diagnostic accuracy, interpreting radiological imaging, predicting disease burdens, and deepening the understanding of tuberculosis (TB), chronic obstructive pulmonary disease (COPD), silicosis, pneumoconiosis, and lung fibrosis. The synthesis positions AI as a revolutionary tool within the healthcare system, offering vital implications for healthcare workers, policymakers, and researchers in comprehending and leveraging AI's pivotal role in lung disease management.
PubMed: 38313926
DOI: 10.7759/cureus.51581