Leukemia

Predicting chemo-brain in breast cancer survivors using multiple MRI features and machine-learning.

PURPOSE: Breast cancer (BC) is the most common cancer in women worldwide. There exist various advanced chemotherapy drugs for BC; however, chemotherapy drugs may result in brain damage during treatment. When a patient's brain is changed in response to chemo drugs, it is termed chemo-brain. In this study, we aimed to construct machine-learning models to detect the subtle alternations of the brain i...

Segmentation of the Proximal Femur from MR Images using Deep Convolutional Neural Networks.

Magnetic resonance imaging (MRI) has been proposed as a complimentary method to measure bone quality and assess fracture risk. However, manual segmentation of MR images of bone is time-consuming, limiting the use of MRI measurements in the clinical practice. The purpose of this paper is to present an automatic proximal femur segmentation method that is based on deep convolutional neural networks (...

Orthotopic Liver Transplantation After Stereotactic Body Radiotherapy for Pediatric Hepatocellular Carcinoma with Central Biliary Obstruction and Nodal Involvement.

Here we describe the case of a 10-year-old boy with a history of chronic hepatitis B who was diagnosed with hepatocellular carcinoma (HCC) with a larg...

Classification of acute lymphoblastic leukemia using deep learning.

Acute Leukemia is a life-threatening disease common both in children and adults that can lead to death if left untreated. Acute Lymphoblastic Leukemia...

Clinically validated machine learning algorithm for detecting residual diseases with multicolor flow cytometry analysis in acute myeloid leukemia and myelodysplastic syndrome.

BACKGROUND: Multicolor flow cytometry (MFC) analysis is widely used to identify minimal residual disease (MRD) after treatment for acute myeloid leuke...

Regression Convolutional Neural Network for Automated Pediatric Bone Age Assessment From Hand Radiograph.

Skeletal bone age assessment is a common clinical practice to investigate endocrinology, and genetic and growth disorders of children. However, clinic...

Structure and Protein Interaction-Based Gene Ontology Annotations Reveal Likely Functions of Uncharacterized Proteins on Human Chromosome 17.

Understanding the function of human proteins is essential to decipher the molecular mechanisms of human diseases and phenotypes. Of the 17 470 human p...

Robotic Assessment of Motor, Sensory, and Cognitive Function in Acute Sport-Related Concussion and Recovery.

There is a need for better tools to objectively, reliably, and precisely assess neurological function after sport-related concussion (SRC). The aim of...

The application of convolution neural network based cell segmentation during cryopreservation.

For most of the cells, water permeability and plasma membrane properties play a vital role in the optimal protocol for successful cryopreservation. Me...

Prediction of postoperative disease-free survival and brain metastasis for HER2-positive breast cancer patients treated with neoadjuvant chemotherapy plus trastuzumab using a machine learning algorithm.

PURPOSE: This study aimed to develop mathematical tools to predict the likelihood of recurrence after neoadjuvant chemotherapy (NAC) plus trastuzumab ...

A Novel Morphological Analysis of DXA-DICOM Images by Artificial Neural Networks for Estimating Bone Mineral Density in Health and Disease.

One of the best methods for diagnosing bone disease in humans is site-specific and total bone mineral density (BMD) measurements by Dual-energy X-ray ...

The Elephant in the Room: Outbreak of Carfentanil Deaths in Minnesota and the Importance of Multiagency Collaboration.

Over a three-month period in early 2017, the Hennepin County Medical Examiner's Office investigated nine apparent opioid toxicity deaths that occurred...

Study on screening potential allergenic proteins from infant milk powders based on human mast cell membrane chromatography and histamine release assays.

Cow's milk allergy is mainly observed in infants and young children. Most allergic reactions affect the skin, followed by the gastrointestinal and res...

CeO Nanoparticles-Loaded pH-Responsive Microparticles with Antitumoral Properties as Therapeutic Modulators for Osteosarcoma.

Osteosarcoma is an aggressive form of bone cancer mostly affecting young people. To date, the most effective strategy for the treatment of osteosarcom...

Increased vitamin B levels in children with zinc deficiency.

Additional nutritional deficiencies may accompany zinc deficiency. We determined the vitamin B levels in patients with zinc (Zn) deficiency. This retr...

Immunomarker Support Vector Machine Classifier for Prediction of Gastric Cancer Survival and Adjuvant Chemotherapeutic Benefit.

Current tumor-node-metastasis (TNM) staging system cannot provide adequate information for prediction of prognosis and chemotherapeutic benefits. We ...

Effect of Hepatitis C Treatment on Renal Function in Liver Transplant Patients.

Hepatitis C Virus (HCV) is uniformly recurrent after liver transplant (LT) and recurrence is associated with an increased risk of mortality. Immunosu...

Framework of Computer Aided Diagnosis Systems for Cancer Classification Based on Medical Images.

Early detection of cancer can increase patients' survivability and treatment options. Medical images such as Mammogram, Ultrasound, Magnetic Resonance...

Drug response prediction by ensemble learning and drug-induced gene expression signatures.

Chemotherapeutic response of cancer cells to a given compound is one of the most fundamental information one requires to design anti-cancer drugs. Rec...

Development and Application of a Machine Learning Approach to Assess Short-term Mortality Risk Among Patients With Cancer Starting Chemotherapy.

IMPORTANCE: Patients with cancer who die soon after starting chemotherapy incur costs of treatment without the benefits. Accurately predicting mortali...