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"Cancer research"
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Computer-assisted medical image classification for early diagnosis of oral cancer employing deep learning algorithm
PurposeOral cancer is a complex wide spread cancer, which has high severity. Using advanced technology and deep learning algorithm early detection and classification are made possible. Medical imaging technique, computer-aided diagnosis and detection can make potential changes in cancer treatment. In this research work, we have developed a deep learning algorithm for automated, computer-aided oral cancer detecting system by investigating patient hyperspectral images.MethodsTo validate the proposed regression-based partitioned deep learning algorithm, we compare the performance with other techniques by its classification accuracy, specificity, and sensitivity. For the accurate medical image classification objective, we demonstrate a new structure of partitioned deep Convolution Neural Network (CNN) with two partitioned layers for labeling and classify by labeling region of interest in multidimensional hyperspectral image.ResultsThe performance of the partitioned deep CNN was verified by classification accuracy. We have obtained classification accuracy of 91.4% with sensitivity 0.94 and a specificity of 0.91 for 100 image data sets training for task classification of cancerous tumor with benign and for task classification of cancerous tumor with normal tissue accuracy of 94.5% for 500 training patterns was obtained.ConclusionsWe compared the obtained results from another traditional medical image classification algorithm. From the obtained result, we identify that the quality of diagnosis is increased by proposed regression-based partitioned CNN learning algorithm for a complex medical image of oral cancer diagnosis.
Journal Article
Male breast cancer in BRCA1 and BRCA2 mutation carriers: pathology data from the Consortium of Investigators of Modifiers of BRCA1/2
Background
BRCA1
and, more commonly,
BRCA2
mutations are associated with increased risk of male breast cancer (MBC). However, only a paucity of data exists on the pathology of breast cancers (BCs) in men with
BRCA1/2
mutations. Using the largest available dataset, we determined whether MBCs arising in
BRCA1/2
mutation carriers display specific pathologic features and whether these features differ from those of
BRCA1/2
female BCs (FBCs).
Methods
We characterised the pathologic features of 419
BRCA1/2
MBCs and, using logistic regression analysis, contrasted those with data from 9675
BRCA1/2
FBCs and with population-based data from 6351 MBCs in the Surveillance, Epidemiology, and End Results (SEER) database.
Results
Among
BRCA2
MBCs, grade significantly decreased with increasing age at diagnosis (
P
= 0.005). Compared with
BRCA2
FBCs,
BRCA2
MBCs were of significantly higher stage (
P
for trend = 2 × 10
−5
) and higher grade (
P
for trend = 0.005) and were more likely to be oestrogen receptor–positive [odds ratio (OR) 10.59; 95 % confidence interval (CI) 5.15–21.80] and progesterone receptor–positive (OR 5.04; 95 % CI 3.17–8.04). With the exception of grade, similar patterns of associations emerged when we compared
BRCA1
MBCs and FBCs.
BRCA2
MBCs also presented with higher grade than MBCs from the SEER database (
P
for trend = 4 × 10
−12
).
Conclusions
On the basis of the largest series analysed to date, our results show that
BRCA1
/
2
MBCs display distinct pathologic characteristics compared with
BRCA1
/
2
FBCs, and we identified a specific
BRCA2-
associated MBC phenotype characterised by a variable suggesting greater biological aggressiveness (i.e., high histologic grade). These findings could lead to the development of gender-specific risk prediction models and guide clinical strategies appropriate for MBC management.
Journal Article
The cancer chronicles : unlocking medicine's deepest mystery
Deftly excavating and illuminating decades of investigation and analysis, rooted in every discipline from evolutionary biology to game theory and physics, Johnson explores what we know--and what we still don't--about cancer, and why a cure remains such a slippery goal.
Book
The comparison between adenocarcinoma and squamous cell carcinoma in lung cancer patients
BackgroundThere are several studies comparing the difference between adenocarcinoma (AC) and squamous cell carcinoma (SqCC) of lung cancer. However, seldom studies compare the different overall survival (OS) between AC and SqCC at same clinical or pathological stage. The aim of the study was to investigate the 5-year OS between AC and SqCC groups.MethodsData were obtained from the Taiwan Society of Cancer Registry. There were 48,296 non-small cell lung cancer (NSCLC) patients analyzed between 2009 and 2014 in this retrospective study. We analyzed both the AC and SqCC groups by age, gender, smoking status, Charlson co-morbidity index (CCI) score, clinical TNM stage, pathological stage, tumor location, histologic grade, pleura invasion, performance status, treatment, stage-specific 5-year OS rate in each clinical stage I–IV and causes of death. We used propensity score matching to reduce the bias.ResultsThe AC and SqCC groups are significantly different in age, gender, smoking status, CCI score, clinical TNM stage, pathological stage, tumor location, histologic grade, pleura invasion, performance status, treatment, stage-specific 5-year OS rate in each clinical stage and causes of death (p < 0.0001). The stage-specific 5-year OS rates between AC and SqCC were 79% vs. 47% in stage I; 50% vs. 32% in stage II; 27% vs. 13% in stage III; 6% vs. 2% in stage IV, respectively (all p values < 0.0001).ConclusionsAC and SqCC have significantly different outcomes in lung cancer. We suggest that these two different cancers should be analyzed separately to provide more precise outcomes in the future.
Journal Article
Cancerland : a medical memoir
\"By exploring the science of cancer, the promising new therapies, and remarkable drugs, Dr. Scadden humanizes it, reveals that progress toward a cure is real--if fitful--and assures those with cancer that they never walk alone\"--Dust jacket flap.
BOOK
TP53 mutations as potential prognostic markers for specific cancers: analysis of data from The Cancer Genome Atlas and the International Agency for Research on Cancer TP53 Database
PurposeMutations in the tumor suppressor gene TP53 are associated with a variety of cancers. Therefore, it is important to know the occurrence and prognostic effects of TP53 mutations in certain cancers.MethodsOver 29,000 cases from the April 2016 release of the International Agency for Research on Cancer (IARC) TP53 Database were analyzed to determine the distribution of germline and somatic mutations in the TP53 gene. Subsequently, 7,893 cancer cases were compiled in cBioPortal for Cancer Genomics from the 33 most recent The Cancer Genome Atlas (TCGA) studies to determine the prevalence of TP53 mutations in cancers and their effects on survival and disease-free survival times.ResultsThe data were analyzed, and it was found that the majority of TP53 mutations were missense and the major mutational hotspots were located at codons 248, 273, 175, and 245 in exons 4–8 for somatic mutations with the addition of codon 337 and other mutations in exons 9–10 for germline mutations. Out of 33 TGCA studies, the effects of TP53 mutations were statistically significant in nine cancers (lung adenocarcinoma, hepatocellular carcinoma, head and neck squamous cell carcinoma, acute myeloid leukemia, clear cell renal cell carcinoma (RCC), papillary RCC, chromophobe RCC, uterine endometrial carcinoma, and thymoma) for survival time and in five cancers (pancreatic adenocarcinoma, hepatocellular carcinoma, chromophobe RCC, acute myeloid leukemia, and thymoma) for disease-free survival time. It was also found that the most common p53 mutation in hepatocellular carcinomas (R249S) was a much better indicator for poor prognosis than TP53 mutations as a whole. In addition, in cases of ovarian serous cystadenocarcinoma, the co-occurrence of TP53 and BRCA mutations resulted in longer survival and disease-free survival times than the presence of neither TP53 nor BRCA mutations.ConclusionTP53 mutations are potential prognostic markers that can be used to further improve the accuracy of predicting survival and disease-free survival times of cancer patients.
Journal Article
The immortal life of Henrietta Lacks
Documents the story of how scientists took cells from an unsuspecting descendant of freed slaves and created a human cell line that has been kept alive indefinitely, enabling discoveries in such areas as cancer research, in vitro fertilization, and gene mapping.
BOOK
Correlations between microsatellite instability and the biological behaviour of tumours
PurposeMicrosatellites are widely distributed repetitive DNA motifs, accounting for approximately 3% of the genome. Due to mismatch repair system deficiency, insertion or deletion of repetitive units often occurs, leading to microsatellite instability. In this review, we aimed to explore the relationship between MSI and biological behaviour of colorectal carcinoma, gastric carcinoma, lymphoma/leukaemia and endometrial carcinoma, as well as the application of frameshift peptide vaccines in cancer therapy.MethodsThe relevant literature from PubMed and Baidu Xueshu were reviewed in this article. The ClinicalTrials.gov database was searched for clinical trials related to the specific topic.ResultsMicrosatellite instability is divided into three subtypes: high-level, low-level microsatellite instability, and stable microsatellites. The majority of tumour patients with high-level microsatellite instability often show a better efficacy and prognosis than those with low-level microsatellite instability or stable microsatellites. In coding regions, especially for genes involved in tumourigenesis, microsatellite instability often results in inactivation of proteins and contributes to tumourigenesis. Moreover, the occurrence of microsatellite instability in coding regions can also cause the generation of frameshift peptides that are thought to be unknown and novel to the individual immune system. Thus, these frameshift peptides have the potential to be biomarkers to raise tumour-specific immune responses.ConclusionMSI has the potential to become a key predictor for evaluating the degree of malignancy, efficacy and prognosis of tumours. Clinically, MSI patterns will provide more valuable information for clinicians to create optimal individualized treatment strategies based on frameshift peptides vaccines.
Journal Article