EliasHossain/CancerAbstracts huggingface dataset:
Category: Thyroid_Cancer
The number of studies on venous thromboembolism (VTE) and thyroid cancer is very scarce and existing data are contradictory. This paper reviews VTE in thyroid cancer.
Category: Generic
In this paper, we identify and review key challenges to bridge the knowledge-gap between SME's, companies, organisations, businesses, government institutions and the general public in adopting, promoting and utilising Blockchain technology. The challenges indicated are Cybersecurity and Data privacy in this instance. Additional challenges are set out supported by literature, in researching data security management systems and legal frameworks to ascertaining the types and varieties of valid encryption, data acquisition, policy and outcomes under ISO 27001 and the General Data Protection Regulations. Blockchain, a revolutionary method of storage and immutability, provides a robust storage strategy, and when coupled with a Smart Contract, gives users the ability to form partnerships, share information and consent via a legally-based system of carrying out business transactions in a secure digital domain. Globally, ethical and legal challenges significantly differ; consent and trust in the public and private sectors in deploying such defensive data management strategies, is directly related to the accountability and transparency systems in place to deliver certainty and justice. Therefore, investment and research in these areas is crucial to establishing a dialogue between nations to include health, finance and market strategies that should encompass all levels of society. A framework is proposed with elements to include Big Data, Machine Learning and Visualisation methods and techniques. Through the literature we identify a system necessary in carrying out experiments to detect, capture, process and store data. This includes isolating packet data to inform levels of Cybersecurity and privacy-related activities, and ensuring transparency demonstrated in a secure, smart and effective manner.
Category: Generic
During the COVID-19 pandemic, more than ever, data science has become a powerful weapon in combating an infectious disease epidemic and arguably any future infectious disease epidemic. Computer scientists, data scientists, physicists and mathematicians have joined public health professionals and virologists to confront the largest pandemic in the century by capitalizing on the large-scale 'big data' generated and harnessed for combating the COVID-19 pandemic. In this paper, we review the newly born data science approaches to confronting COVID-19, including the estimation of epidemiological parameters, digital contact tracing, diagnosis, policy-making, resource allocation, risk assessment, mental health surveillance, social media analytics, drug repurposing and drug development. We compare the new approaches with conventional epidemiological studies, discuss lessons we learned from the COVID-19 pandemic, and highlight opportunities and challenges of data science approaches to confronting future infectious disease epidemics. This article is part of the theme issue 'Data science approaches to infectious disease surveillance'.
Category: Generic
Radiation oncology, a major treatment modality in the care of patients with malignant disease, is a technology- and computer-intensive medical specialty. As such, it should lend itself ideally to data science methods, where computer science, statistics, and clinical knowledge are combined to advance state-of-the-art care. Nevertheless, data science methods in radiation oncology research are still in their infancy and successful applications leading to improved patient care remain scarce. Here, we discuss data interoperability issues within and across organizational boundaries that hamper the introduction of big data and data science techniques in radiation oncology. At the semantic level, creating common underlying models and codification of the data, including the use of data elements with standardized definitions, an ontology, remains a work in progress. Methodological issues in data science and in the use of large population-based health data registries are identified. We show that data science methods and big data cannot replace randomized clinical trials in comparative effectiveness research by reviewing a series of instances where the outcomes of big data analyses and randomized trials are at odds. We also discuss the modern wave of machine learning and artificial intelligence as represented by deep learning and convolutional neural networks. Finally, we identify promising research avenues and remain optimistic that the data sources in radiation oncology can be linked to yield important insights in the near future. We argue that data science will be a valuable complement to, but not a replacement of, the traditional hypothesis-driven translational research chain and the randomized clinical trials that form the backbone of evidence-based medicine.
Category: Lung_Cancer
Lung cancer is a complex problem because there are a number of different histological cell types. Those commonly grouped as bronchogenic carcinoma (epidermoid carcinoma, adenocarcinoma, large cell undifferentiated carcinoma, small cell carcinoma, and adenosquamous carcinoma) account for more than 90% of the new cases and the deaths each year. The natural history of bronchogenic carcinoma suggests that many years pass while the cancer evolves from a pre-cancerous change in the bronchial mucosa, to undetectable microscopic cancer, to preclinical asymptomatic cancer and finally into a full symptomatic cancer, the phase of most lung malignancies in the tissue at diagnosis. Therefore, students of the aetiology of this disease must consider what has happened to patients 5-20 years before lung cancer is diagnosed.
Category: Thyroid_Cancer
The diagnosis and management of follicular carcinoma of the thyroid gland remains a controversial topic. Color-Doppler (CD) imaging has been expected for the differential diagnosis between follicular adenoma and follicular carcinoma. CD imaging examination of follicular tumors has revealed that high-velocity pulsative blood flow penetrating the tumor is a characteristic finding of follicular carcinoma. Real-time tissue elastography (RTE), which enable to demonstrate the tissue elasticity, has begun to be applied for the thyroid disease. In follicular cancer, the difference of elasticity from core of the tumor and periphery is supposed to be depend on the difference of hypercellurality. RTE can provide new useful information for the differential diagnosis of thyroid follicular lesions.
Category: Generic
The convergence of digital pathology and computer vision is increasingly enabling computers to perform tasks performed by humans. As a result, artificial intelligence (AI) is having an astoundingly positive effect on the field of pathology, including breast pathology. Research using machine learning and the development of algorithms that learn patterns from labeled digital data based on "deep learning" neural networks and feature-engineered approaches to analyze histology images have recently provided promising results. Thus far, image analysis and more complex AI-based tools have demonstrated excellent success performing tasks such as the quantification of breast biomarkers and Ki67, mitosis detection, lymph node metastasis recognition, tissue segmentation for diagnosing breast carcinoma, prognostication, computational assessment of tumor-infiltrating lymphocytes, and prediction of molecular expression as well as treatment response and benefit of therapy from routine H&E images. This review critically examines the literature regarding these applications of AI in the area of breast pathology.
Category: Lung_Cancer
A clinicopathological analysis was carried out on 50 cases of lung cancer with silicosis diagnosed from April 1975 to March 1988. All patients were males and the age distribution ranged from 47 to 85 years with a mean of 63.5 at diagnosis. They had been exposed to silica in tunneling for 3 to 42 years, with an average of 15.1. Forty eight cases smoked. Histologically, squamous cell carcinoma was the most common with 29 cases, followed by 10 small cell carcinomas, 6 adenocarcinomas, 4 large cell carcinomas and one adenosquamous carcinoma. Thirty seven tumors were located in peripheral regions, mostly upper lobe or S6, while 13 tumors were in large bronchi. As the most common histological types of lung cancer with silicosis were squamous cell carcinoma and small cell carcinoma, some carcinogens might be involved in tumorigenesis. Silica alone is not considered to be a carcinogen, however, silica containing adsorbed polycyclic aromatic hydrocarbons from cigarette smoking or from industrial pyrolysis can act as a carcinogen or promoter.
Category: Colon_Cancer
Introduction: Abdominal actinomycosis is a rare granulomatous inflammatory disease caused by a Gram-positive anaerobic bacterium Actinomyces israelii, manifesting as inflammatory mass, or abscess formation. Evolution is slow and steady in inflammatory contiguous extension without limit organ that lends itself to confusion with abdominal malignancies. Methods: We performed a retrospective study on the patients with abdominal actinomycosis operated in the First Surgical Clinic, "St. Spiridon" University Hospital Iasi; between 1980 - 2018 there have been 13 cases (4 men and 9 women) with a mean age 44.07 years admitted for abdominal tumors (7 cases) or pelvic inflammatory disease (6 cases). Results: We identified as predisposing factors: IUD maintained over 10 years (6 cases), foreign bodies 2 cases (a toothpick probably perforated colon, gallstones lost in peritoneum), diabetes (3 cases), immunodepression. All cases were operated by laparotomy (9 cases) or laparoscopic approach (4 cases). We describe five of these cases of actinomycosis that had been mimicking a colon cancer: ileo - cecal - 3 cases, transverse colon - one case and on the greater omentum - one case, followed by specific treatment with penicillin, with good evolution. Conclusions: Abdominal actinomycosis should always be included in the differential diagnosis of abdominal tumors. Preoperative diagnosis, difficult but possible, can avoid surgery. Treatment with antibiotics is necessary for the healing of the disease. Postoperative control is mandatory, with relapses possible.
Category: Lung_Cancer
It has been suggested that protective factors might explain the differential incidence of lung cancer within a given population. Changes in diet, for example, might modulate neoplastic cell formation, since food contains many modifiers of carcinogenesis. The number of studies carried out so far does not permit to draw final conclusions yet. Interesting topics to be discussed include substances which doubtlessly play no role whatsoever for the prevention of lung cancer, like vitamin C, and those which seemingly do, like selenium. Still others consist in cholesterol, vitamins A and E, for which data are either controversial or, at present, still scanty. Moreover, the paper reviews the importance of interactions among nutrients for their effects on cancer risk. Considering major studies in this field, the review puts into evidence the principal results of research carried out so far.
Category: Thyroid_Cancer
The prevalence of low-risk differentiated thyroid cancer (DTC) is dramatically increasing because of superior diagnostic imaging technologies. Remote-access endoscopic thyroidectomy is becoming more popular for the lack of a noticeable neck scar. Transoral endoscopic thyroidectomy, vestibular approach (TOETVA) is the only technique that could be called a true scarless surgery; however, there is a scarcity of long-term studies about its safety and feasibility. Because thyroid cancer is a slow-growing lesion, with adequate follow-up and surveillance, TOETVA is a surgical procedure for the management of low-risk DTC without any difference of surgical and oncological outcome.
Category: Lung_Cancer
Cytokines are hormonE-like proteins and peptides involved in the signalling between cells during immune response. They are produced mainly by lymphocytes (lymphokines) and mononuclear phagocytes (monokines). They are involved in both cell-mediated and humoral immunity. Cytokines fall into a number of categories: interferons (IFNs), interleukins (ILs) and growth factors. It has been indicated in cancer immunology the following cytokines are particularly important: IFNs, TNF-alpha, IL-1, IL-2, IL-4, IL-6, IL-7, IL-9, IL-10, IL-12. Interferons (IFN-gamma in particular) in cooperation with TNF-alpha and IL-1 inhibit proliferation of tumor cells and by their synergic activity with IL-2 induce cytotoxicity of NK-cells. They activate mononuclear phagocytes and by B lymphocyte stimulation augment lysis of cancer cells. TNF-alpha has mainly cytotoxic activity, leading to hemorrhagic necrosis of tumors. It is also an endogenic pyrogen which is together with IL-1 responsible for pyretic status in neoplastic disease. IL-1 stimulates necrotizing activity of TNF-alpha and augments cachexia by anabolism of lipid induction. IL-2, IL-6 and IL-12 induce NK and LAK-cell cytotoxicity. IL-12 inhibits metastasis formation. IL-10, by inhibiting synthesis of cytokines may lead to tumor development.
Category: Colon_Cancer
The role of laparoscopic resection in the management of colon cancer is still a subject of debate. In this clinical study, we compared the perioperative results and long-term outcome for two unselected groups of patients undergoing either laparoscopic or open hemicolectomy for colon cancer.
Category: Lung_Cancer
Sera from 171 patients with advanced lung cancer, from 110 normals, and from 123 subjects with benign respiratory diseases were analyzed for 10 substances to detect lung cancer: ferritin, lipid-bound sialic acid, total sialic acid, beta 2-microglobulin, lipotropin, the alpha and beta subunits of human chorionic gonadotropin, calcitonin (two assays), parathyroid hormone, and carcinoembryonic antigen. Individual markers were studied, and optimal combinations of markers were sought for discriminating lung cancer patients from normals and from patients with benign lung disease. Numerous methods for combining the markers were examined, but the methods of logistic regression and recursive partitioning were finally adopted. The best discrimination rules we could find used only carcinoembryonic antigen (CEA) and total sialic acid (TSA). The performance of these rules was validated on an independent serum panel containing sera from 68 patients with advanced lung cancer, from 40 normals, and from 52 patients with benign respiratory disease. The combination rules based on TSA and CEA performed better than a rule based on CEA alone. Logistic discrimination rules with TSA and CEA that were designed to have 95% specificity achieved 54% sensitivity for discriminating advanced lung cancer from normal controls and 52% sensitivity for discriminating advanced lung cancer from controls with benign disease. Some aspects of clinical applicability are discussed, including planned studies for localized lung cancer and the requirement for further testing in specific clinical settings.
Category: Generic
Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. These methods have dramatically improved the state-of-the-art in speech recognition, visual object recognition, object detection and many other domains such as drug discovery and genomics. Deep learning discovers intricate structure in large data sets by using the backpropagation algorithm to indicate how a machine should change its internal parameters that are used to compute the representation in each layer from the representation in the previous layer. Deep convolutional nets have brought about breakthroughs in processing images, video, speech and audio, whereas recurrent nets have shone light on sequential data such as text and speech.
Category: Generic
Recent advances in data science are impacting the development of classical force fields. Here we review some ideas and techniques from data science that have been used in force field development, including database construction, atom typing, and machine learning potentials. We highlight how new tools such as active learning and automatic differentiation are facilitating the generation of target data and the direct fitting with macroscopic observables. Philosophical changes on how force field models should be built and used are also discussed. It's inspiring that more accurate biomolecular force fields can be developed with the aid of data science techniques.
Category: Lung_Cancer
Lung cancer continues to be one of the most common causes of cancer death despite understanding the major cause of the disease: cigarette smoking. Smoking increases lung cancer risk 5- to 10-fold with a clear dose-response relationship. Exposure to environmental tobacco smoke among nonsmokers increases lung cancer risk about 20%. Risks for marijuana and hookah use, and the new e-cigarettes, are yet to be consistently defined and will be important areas for continued research as use of these products increases. Other known environmental risk factors include exposures to radon, asbestos, diesel, and ionizing radiation. Host factors have also been associated with lung cancer risk, including family history of lung cancer, history of chronic obstructive pulmonary disease and infections. Studies to identify genes associated with lung cancer susceptibility have consistently identified chromosomal regions on 15q25, 6p21 and 5p15 associated with lung cancer risk. Risk prediction models for lung cancer typically include age, sex, cigarette smoking intensity and/or duration, medical history, and occupational exposures, however there is not yet a risk prediction model currently recommended for general use. As lung cancer screening becomes more widespread, a validated model will be needed to better define risk groups to inform screening guidelines.
Category: Lung_Cancer
The diagnosis and treatment of lung cancer (LC) is always a challenge. The difficulty in the decision of therapeutic schedule and diagnosis is directly related to intratumoral heterogeneity (ITH) in the progression of LC. It has been proven that most tumors emerge and evolve under the pressure of their living microenvironment, which involves genetic, immunological, metabolic, and therapeutic components. While most research on ITH revealed multiple mechanisms and characteristic, a systemic exposition of ITH in LC is still hard to find. In this review, we describe how ITH in LC develops from the perspective of space and time. We discuss elaborate details and affection of every aspect of ITH in LC and the relationship between them. Based on ITH in LC, we describe a more accurate multidisciplinary therapeutic strategy on LC and provide the newest opinion on the potential approach of LC therapy.
Category: Generic
Metalloproteins are a family of proteins characterized by metal ion binding, whereby the presence of these ions confers key catalytic and ligand-binding properties. Due to their ubiquity among biological systems, researchers have made immense efforts to predict the structural and functional roles of metalloproteins. Ultimately, having a comprehensive understanding of metalloproteins will lead to tangible applications, such as designing potent inhibitors in drug discovery. Recently, there has been an acceleration in the number of studies applying machine learning to predict metalloprotein properties, primarily driven by the advent of more sophisticated machine learning algorithms. This review covers how machine learning tools have consolidated and expanded our comprehension of various aspects of metalloproteins (structure, function, stability, ligand-binding interactions, and inhibitors). Future avenues of exploration are also discussed.
Category: Lung_Cancer
Advances in imaging technologies and biomarker research offer hope that the incidence and mortality of lung cancer can be reduced by screening similar to what have been achieved for cancer of the cervix, breast, and colon.
Category: Colon_Cancer
Epidemiologic and laboratory studies suggest a cancer protective effect and/or lack of a tumor promoting effect by dietary olive oil as compared with other types of non-marine oils. Squalene, a constituent of olive oil, and a key intermediate in cholesterol synthesis may be regarded as partially responsible for the beneficial effects of olive oil, which include decreased mortality rates among populations with high olive oil consumption. Thus, in this study we have assessed the chemopreventive efficacy of squalene on azoxymethane (AOM)-induced colonic aberrant crypt foci (ACF). In addition, we measured the effect of squalene on serum cholesterol levels in the rats. Male F34 rats (5 weeks old) were fed the control diet (modified AIN-76A) or experimental diets containing 1% squalene or 320 p.p.m. sulindac. Two weeks later, all animals except those in vehicle (normal saline)-treated groups were s.c. injected with AOM (15 mg/kg body wt, once weekly for 2 weeks). At 16 weeks of age, all rats were killed, colons were evaluated for ACF and serum was assayed for the cholesterol levels. As expected, dietary administration of sulindac suppressed ACF development and reduced crypt multiplicity, i.e. number of aberrant crypts/focus. Administration of dietary squalene inhibited total ACF induction and crypt multiplicity by approximately >46% (P < 0.001). Further, squalene at a level of 1% did not show any significant effect on serum cholesterol levels. Our finding that squalene significantly suppresses colonic ACF formation and crypt multiplicity strengthens the hypothesis that squalene possesses chemopreventive activity against colon carcinogenesis.
Category: Lung_Cancer
The diagnosis, staging, and follow-up of lung cancer is a clinical and therapeutic challenge. Recent radiographic advances are critical to the management of patients with lung cancer. This review focuses on state-of-the-art chest imaging modalities, including plain radiography, computed tomography; magnetic resonance imaging, as well as the newest technique, positron-emission tomography, and discusses the current literature.
Category: Colon_Cancer
Identification of new prognostic factors for colon cancer with no lymph node involvement may improve the selection of patients for adjuvant chemotherapy. The aim of this study was to assess the possibility of using gene expression profiling for this purpose. Fifty patients operated on for stage II colon cancer were included. Twenty-five of these patients relapsed, while the other 25 remained disease-free for at least 5 years. MRNA was extracted from fresh-frozen biopsies and hybridized to the Affymetrix GeneChip HGU133A. One thousand six hundred random splits of the 50 patients into a training set and a validation set were considered. For each split, a prognostic combination was derived from the training set (selection of the 30 genes most differentially expressed between patients who recurred and those who did not, by linear discriminant analysis), and its prognostic performance was assessed with the validation set. On average, accuracy was 76%, sensitivity 85%, and specificity 68%. A total of 6,124 genes were included in at least one of the 1,600 predictive combinations, and 55 genes were included in more than 100 combinations. This study supports the possibility of predicting the prognosis of non-metastatic colon cancer by tumor gene expression profiling. It also shows the highly variable gene composition of predictive combinations.