Breast cancer detection using ensemble of convolutional neural networks

Early detection leading to timely treatment in the initial stages of cancer may decrease the breast cancer death rate. We propose deep learning techniques along with image processing for the detection of tumors. The availability of online datasets and advances in graphical processing units (GPU) have promoted the application of deep learning models for the detection of breast cancer. In this paper, deep learning models using convolutional neural network (CNN) have been built to automatically classify mammograms into benign and malignant. Issues like overfitting and dataset imbalance are overcome. Experimentation has been done on two publicly available datasets, namely mammographic image analysis society (MIAS) database and digital database for screening mammography (DDSM). Robustness of the models is accomplished by merging the datasets. In our experimentation, MatConvNet has achieved an accuracy of 94.2% on the merged dataset, performing the best amongst all the CNN models used individually. Hungarian optimization algorithm is employed for selection of individual CNN models to form an ensemble. Ensemble of CNN models led to an improved performance, resulting in an accuracy of 95.7%

Labelling of DOTA-Tyr(3)-octreotate by oxidative iodination

SOUHRN Značení DOTA-Tyr(3)-oktreotátu oxidativní jodací Diplomová práce Klára Tvrdíková Univerzita Karlova v Praze, Farmaceutická fakulta v Hradci Králové Katedra biofyziky a fyzikální chemie V této diplomové práci byla vyzkoušena metoda značení somatostatinového analogu DOTA-Tyr3 -octreotátu radioaktivním jódem. Peptid byl značen přímou elektrofilní substitucí a jako oxidační činidlo byl použit chloramin-T. Ten oxiduje jodid na aktivní kationy jódu, které jsou pak začleněny do tyrosinových částí peptidu. K oddělení značeného peptidu a nenavázaného radioaktivního jódu byly použity dvě metody, extrakce na pevné fázi (Sep-Pak Vac 1 cc, C 18 Cartridges) a vysokoúčinná kapalinová chromatografie (Lichrocart Lichrospher C-18, 250 x 4 mm, 5 m). HPLC metoda je výhodnější, jelikož odstraní nenavázaný jodid a zároveň di-jodované deriváty. Dále byla zkoušena stabilita a farmakokinetické vlastnosti radioaktivně značeného DOTA-Tyr3 -octreotátu. Výsledky biodistribučních studií naznačily poměrně rychlou eliminaci jodovaného peptidu z ledvin a z orgánů s vysokou hustotou somatostatinových receptorů (pankreas, nadledviny).Katedra biofyziky a fyzikální chemieDepartment of Biophysics and Physical ChemistryFaculty of Pharmacy in Hradec KrálovéFarmaceutická fakulta v Hradci Králov

Additional file 1: of The prognostic importance of duration of AKI: a systematic review and meta-analysis

Systematic review search strategy. (DOC 24 kb

Additional file 4: of The prognostic importance of duration of AKI: a systematic review and meta-analysis

Separate forest plot for long term mortality with transient and persistent duration of AKI. (TIFF 72 kb

Additional file 2: of The prognostic importance of duration of AKI: a systematic review and meta-analysis

Quality Assessment. (XLSX 17 kb

National Trends and Impact of Acute Kidney Injury Requiring Hemodialysis in Hospitalizations With Atrial Fibrillation

BACKGROUND: Atrial fibrillation (AF) is a common cause for hospitalization, but there are limited data regarding acute kidney injury requiring dialysis (AKI‐D) in AF hospitalizations. We aimed to assess temporal trends and outcomes in AF hospitalizations complicated by AKI‐D utilizing a nationally representative database. METHODS AND RESULTS: Utilizing the Nationwide Inpatient Sample, AF hospitalizations and AKI‐D were identified using diagnostic and procedure codes. Trends were analyzed overall and within subgroups and utilized multivariable logistic regression to generate adjusted odds ratios (aOR) for predictors and outcomes including mortality and adverse discharge. Between 2003 and 2012, 3751 (0.11%) of 3 497 677 AF hospitalizations were complicated by AKI‐D. The trend increased from 0.3/1000 hospitalizations in 2003 to 1.5/1000 hospitalizations in 2012, with higher increases in males and black patients. Temporal changes in demographics and comorbidities explained a substantial proportion but not the entire trend. Significant comorbidities associated with AKI‐D included mechanical ventilation (aOR 13.12; 95% CI 9.88‐17.43); sepsis (aOR 8.20; 95% CI 6.00‐11.20); and liver failure (aOR 3.72; 95% CI 2.92‐4.75). AKI‐D was associated with higher risk of in‐hospital mortality (aOR 3.54; 95% CI 2.81‐4.47) and adverse discharge (aOR 4.01; 95% CI 3.12‐5.17). Although percentage mortality within AKI‐D decreased over the decade, attributable risk percentage mortality remained stable. CONCLUSIONS: AF hospitalizations complicated by AKI‐D have quintupled over the last decade with differential increase by demographic groups. AKI‐D is associated with significant morbidity and mortality. Without effective AKI‐D therapies, focus should be on early risk stratification and prevention to avoid this devastating complication

National Trends and Impact of Acute Kidney Injury Requiring Hemodialysis in Hospitalizations With Atrial Fibrillation.

Atrial fibrillation (AF) is a common cause for hospitalization, but there are limited data regarding acute kidney injury requiring dialysis (AKI-D) in AF hospitalizations. We aimed to assess temporal trends and outcomes in AF hospitalizations complicated by AKI-D utilizing a nationally representative database. Utilizing the Nationwide Inpatient Sample, AF hospitalizations and AKI-D were identified using diagnostic and procedure codes. Trends were analyzed overall and within subgroups and utilized multivariable logistic regression to generate adjusted odds ratios (aOR) for predictors and outcomes including mortality and adverse discharge. Between 2003 and 2012, 3751 (0.11%) of 3 497 677 AF hospitalizations were complicated by AKI-D. The trend increased from 0.3/1000 hospitalizations in 2003 to 1.5/1000 hospitalizations in 2012, with higher increases in males and black patients. Temporal changes in demographics and comorbidities explained a substantial proportion but not the entire trend. Significant comorbidities associated with AKI-D included mechanical ventilation (aOR 13.12; 95% CI 9.88-17.43); sepsis (aOR 8.20; 95% CI 6.00-11.20); and liver failure (aOR 3.72; 95% CI 2.92-4.75). AKI-D was associated with higher risk of in-hospital mortality (aOR 3.54; 95% CI 2.81-4.47) and adverse discharge (aOR 4.01; 95% CI 3.12-5.17). Although percentage mortality within AKI-D decreased over the decade, attributable risk percentage mortality remained stable. AF hospitalizations complicated by AKI-D have quintupled over the last decade with differential increase by demographic groups. AKI-D is associated with significant morbidity and mortality. Without effective AKI-D therapies, focus should be on early risk stratification and prevention to avoid this devastating complication