Leukemia

The rise and fall of the model for end-stage liver disease score and the need for an optimized machine learning approach for liver allocation.

PURPOSE OF REVIEW: The Model for End-Stage Liver Disease (MELD) has been used to rank liver transplant candidates since 2002, and at the time bringing much needed objectivity to the liver allocation process. However, and despite numerous revisions to the MELD score, current liver allocation still does not allow for equitable access to all waitlisted liver candidates.

Single Center Experience with Robot Technologies for Sterile Compounding: A Retrospective Review.

The compounding of sterile medication admixtures is a labor-intensive process and subject to potential human error. The addition of robotic devices and workflow technology may mitigate some of the challenges of compounding sterile product admixtures, especially for those associated with antineoplastic and hazardous medications. This article discusses the single-center experiences from October 2009...

Deep Learning for Acute Myeloid Leukemia Diagnosis.

By changing the lifestyle and increasing the cancer incidence, accurate diagnosis becomes a significant medical action. Today, DNA microarray is widel...

Analysis of Four Types of Leukemia Using Gene Ontology Term and Kyoto Encyclopedia of Genes and Genomes Pathway Enrichment Scores.

AIM AND OBJECTIVE: Leukemia is the second common blood cancer after lymphoma, and its incidence rate has an increasing trend in recent years. Leukemia...

[Present and future perspectives of artificial intelligence: examples of mathematical approaches for analysis of disease dynamics].

Artificial intelligence (AI) has been applied widely in medicine. For example, deep neural network-based deep learning is particularly effective for p...

Evaluation of genotoxicity after acute and chronic exposure to 2,4-dichlorophenoxyacetic acid herbicide (2,4-D) in rodents using machine learning algorithms.

2,4-Dichlorophenoxyacetic acid (2,4-D) is one of the most widely used herbicides in the world, but its mutagenic and carcinogenic potential is still c...

Diterpenoids from Roots of and Toxicity against Human Cancer Cell Lines.

Further investigations on phytochemical constituents of dichloromethane extract from roots of ( led to the isolation and identification of eight know...

[A Case of Disseminated Carcinomatosis of the Bone Marrow Developing 15 Months after Gastrectomy].

The patient was a 60-year-old man who underwent distal gastrectomy for gastric cancer. The pathological diagnosis was Stage ⅡB. He received adjuvant c...

[A Patient with Multiple Colorectal Liver Metastases for Whom Partial Splenic Embolization Contributed Extremely to Maintain Multidisciplinary Treatment].

After approximately 2.5 years of chemotherapy at the referred hospital, a 69-year-old man with double colon cancer and unresectable liver metastases(H...

[A Case of Breast Cancer Liver Metastases with Jaundice Responding to Chemotherapy].

A 50-year-old woman was referred to our hospital due to breast cancer with multiple liver metastasis diagnosed by CT scan. Laboratory findings showed ...

[Rectal Gastrointestinal Stromal Tumor(GIST)Excised by Two Teams Following Neoadjuvant Chemotherapy-A Case Report].

A 67-year-old man presented with bloody stools. Colonoscopy showed a small submucosal tumor in the lower rectum. As the tumor was small, follow-up was...

[Stage Ⅳ Breast Cancer with Difficulty in Initiating Chemotherapy-A Case Report].

We report a case of breast cancer(T4b[skin], N1, M1[lung], ER-, PR-, HER2 3+)in a 63-year-old woman with liver dysfunction of unknown cause(T-Bil 3.6m...

Prior to Initiation of Chemotherapy, Can We Predict Breast Tumor Response? Deep Learning Convolutional Neural Networks Approach Using a Breast MRI Tumor Dataset.

We hypothesize that convolutional neural networks (CNN) can be used to predict neoadjuvant chemotherapy (NAC) response using a breast MRI tumor datase...

A BLSTM with Attention Network for Predicting Acute Myeloid Leukemia Patient's Prognosis using Comprehensive Clinical Parameters.

The prognosis management is crucial for highrisk disease like Acute Myeloid Leukemia (AML) in order to support decisions of clinical treatment. Howeve...

Improved Interpretability of Machine Learning Model Using Unsupervised Clustering: Predicting Time to First Treatment in Chronic Lymphocytic Leukemia.

PURPOSE: Time to event is an important aspect of clinical decision making. This is particularly true when diseases have highly heterogeneous presentat...

A parsimonious 3-gene signature predicts clinical outcomes in an acute myeloid leukemia multicohort study.

Acute myeloid leukemia (AML) is a genetically heterogeneous hematological malignancy with variable responses to chemotherapy. Although recurring cytog...

Deep Learning Approach for Assessment of Bladder Cancer Treatment Response.

We compared the performance of different Deep learning-convolutional neural network (DL-CNN) models for bladder cancer treatment response assessment b...

Impact of Machine Learning With Multiparametric Magnetic Resonance Imaging of the Breast for Early Prediction of Response to Neoadjuvant Chemotherapy and Survival Outcomes in Breast Cancer Patients.

PURPOSE: The aim of this study was to assess the potential of machine learning with multiparametric magnetic resonance imaging (mpMRI) for the early p...

Towards rapid prediction of drug-resistant cancer cell phenotypes: single cell mass spectrometry combined with machine learning.

Combined single cell mass spectrometry and machine learning methods is demonstrated for the first time to achieve rapid and reliable prediction of the...

Victors: a web-based knowledge base of virulence factors in human and animal pathogens.

Virulence factors (VFs) are molecules that allow microbial pathogens to overcome host defense mechanisms and cause disease in a host. It is critical t...