AIMC Topic: Prognosis

Clear Filters Showing 2731 to 2740 of 3837 articles

Breast Microcalcification Diagnosis Using Deep Convolutional Neural Network from Digital Mammograms.

Computational and mathematical methods in medicine
Mammography is successfully used as an effective screening tool for cancer diagnosis. A calcification cluster on mammography is a primary sign of cancer. Early researches have proved the diagnostic value of the calcification, yet their performance is...

Computer aided quantification of intratumoral stroma yields an independent prognosticator in rectal cancer.

Cellular oncology (Dordrecht, Netherlands)
PURPOSE: Tumor-stroma ratio (TSR) serves as an independent prognostic factor in colorectal cancer and other solid malignancies. The recent introduction of digital pathology in routine tissue diagnostics holds opportunities for automated TSR analysis....

Assessment of a Deep Learning Model Based on Electronic Health Record Data to Forecast Clinical Outcomes in Patients With Rheumatoid Arthritis.

JAMA network open
IMPORTANCE: Knowing the future condition of a patient would enable a physician to customize current therapeutic options to prevent disease worsening, but predicting that future condition requires sophisticated modeling and information. If artificial ...

Assessment of Machine Learning vs Standard Prediction Rules for Predicting Hospital Readmissions.

JAMA network open
IMPORTANCE: Hospital readmissions are associated with patient harm and expense. Ways to prevent hospital readmissions have focused on identifying patients at greatest risk using prediction scores.

Predicting life expectancy with a long short-term memory recurrent neural network using electronic medical records.

BMC medical informatics and decision making
BACKGROUND: Life expectancy is one of the most important factors in end-of-life decision making. Good prognostication for example helps to determine the course of treatment and helps to anticipate the procurement of health care services and facilitie...

Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge.

Medical image analysis
Tumor proliferation is an important biomarker indicative of the prognosis of breast cancer patients. Assessment of tumor proliferation in a clinical setting is a highly subjective and labor-intensive task. Previous efforts to automate tumor prolifera...

A Novel Hybrid Feature Extraction Model for Classification on Pulmonary Nodules.

Asian Pacific journal of cancer prevention : APJCP
In this paper an improved Computer Aided Design system can offer a second opinion to radiologists on early diagnosis of pulmonary nodules on CT (Computer Tomography) images. A Deep Convolutional Neural Network (DCNN) method is used for feature extrac...

Machine learning analysis of gene expression data reveals novel diagnostic and prognostic biomarkers and identifies therapeutic targets for soft tissue sarcomas.

PLoS computational biology
Based on morphology it is often challenging to distinguish between the many different soft tissue sarcoma subtypes. Moreover, outcome of disease is highly variable even between patients with the same disease. Machine learning on transcriptome sequenc...

Importance of medical data preprocessing in predictive modeling and risk factor discovery for the frailty syndrome.

BMC medical informatics and decision making
BACKGROUND: Increasing life expectancy results in more elderly people struggling with age related diseases and functional conditions. This poses huge challenges towards establishing new approaches for maintaining health at a higher age. An important ...