AIMC Topic: Machine Learning

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Machine Learning-Supported Analyses Improve Quantitative Histological Assessments of Amyloid-β Deposits and Activated Microglia.

Journal of Alzheimer's disease : JAD
BACKGROUND: Detailed pathology analysis and morphological quantification is tedious and prone to errors. Automatic image analysis can help to increase objectivity and reduce time. Here, we present the evaluation of the DeePathology STUDIO™ for automa...

A Review on Multi-organ Cancer Detection Using Advanced Machine Learning Techniques.

Current medical imaging
Abnormal behaviors of tumors pose a risk to human survival. Thus, the detection of cancers at their initial stage is beneficial for patients and lowers the mortality rate. However, this can be difficult due to various factors related to imaging modal...

DeepSSPred: A Deep Learning Based Sulfenylation Site Predictor Via a Novel nSegmented Optimize Federated Feature Encoder.

Protein and peptide letters
BACKGROUND: S-sulfenylation (S-sulphenylation, or sulfenic acid) proteins, are special kinds of post-translation modification, which plays an important role in various physiological and pathological processes such as cytokine signaling, transcription...

Data Analysis for Antibody Arrays.

Methods in molecular biology (Clifton, N.J.)
When obtaining high-throughput data from antibody arrays, researchers have to face a couple of questions: How and by what means can they get reasonable results significant to their research from these data? Similar to a gene microarray, the classical...

New Perspectives on Machine Learning in Drug Discovery.

Current medicinal chemistry
Artificial intelligence methods, in particular, machine learning, has been playing a pivotal role in drug development, from structural design to the clinical trial. This approach is harnessing the impact of computer-aided drug discovery due to large ...

Potentials of AI in medical image analysis in Gastroenterology and Hepatology.

Journal of gastroenterology and hepatology
With the advancement of artificial intelligence (AI) technology, it comes in a big wave carrying possibly huge impact in the field of medicine. Gastroenterology and hepatology, being a specialty relying much on diagnostic imaging, endoscopy, and hist...

Artificial intelligence in cardiovascular medicine.

Current opinion in cardiology
PURPOSE OF REVIEW: Artificial intelligence is a broad set of sophisticated computer-based statistical tools that have become widely available. Cardiovascular medicine with its large data repositories, need for operational efficiency and growing focus...

A Review on the Role of Artificial Intelligence in Stem Cell Therapy: An Initiative for Modern Medicines.

Current pharmaceutical biotechnology
Stem Cells (SCs) show a wide range of applications in the treatment of numerous diseases, including neurodegenerative diseases, diabetes, cardiovascular diseases, cancer, etc. SC related research has gained popularity owing to the unique characterist...

Development of Machine Learning Models for Predicting Postoperative Delayed Remission in Patients With Cushing's Disease.

The Journal of clinical endocrinology and metabolism
CONTEXT: Postoperative hypercortisolemia mandates further therapy in patients with Cushing's disease (CD). Delayed remission (DR) is defined as not achieving postoperative immediate remission (IR), but having spontaneous remission during long-term fo...

Variable Selection for Time-to-Event Data.

Methods in molecular biology (Clifton, N.J.)
With the increasing availability of large scale biomedical and -omics data, researchers are offered with unprecedented opportunities to discover novel biomarkers for clinical outcomes. At the same time, they are also faced with great challenges to ac...