Oncology/Hematology

[Artificial intelligence and palliative care: opportunities and limitations.].

The so-called artificial intelligence tools applied to palliative care (machine learning, natural language processing) have great potential to support clinicians in improving decision-making processes and in identifying those who are at high risk of mortality or at greater risk of inappropriate treatment and/or non-positive outcomes. The improvement of prognostic abilities may help to avoid that s...

Synthesis and evaluation of a novel nanosized anionic linear globular dendrimer G2-ciprofloxacin conjugate against prostate cancer.

Prostate cancer is the second most common cancer in the world and the fifth cause of cancer deaths in men. Ciprofloxacin enables the inhabitation of the development of prostate cancer. In this regard, we plan to improve the anticancer effect of ciprofloxacin using the anionic G2 dendrimer in conjunction with ciprofloxacin. In the current study, we measured the size and the zeta potential as well a...

Volatile constituents and in vitro activity of Syzygium aromaticum flower buds (clove) against human cancer cell lines.

The methanolic extract (SA-EXT) of Syzygium aromaticum flower buds and its fractions tested against three human cancer cell lines viz uterine cervix (...

[Application of deep learning in cancer prognosis prediction model].

In recent years, deep learning has provided a new method for cancer prognosis analysis. The literatures related to the application of deep learning in...

Common gene signatures and key pathways in hypopharyngeal and esophageal squamous cell carcinoma: Evidence from bioinformatic analysis.

BACKGROUND: Hypopharyngeal and esophageal squamous cell carcinoma (ESCC) are the most common double primary tumors with poor prognosis. Intensive work...

Application of artificial intelligence in the diagnosis and treatment of hepatocellular carcinoma: A review.

Although artificial intelligence (AI) was initially developed many years ago, it has experienced spectacular advances over the last 10 years for appli...

How Does the Skeletal Oncology Research Group Algorithm's Prediction of 5-year Survival in Patients with Chondrosarcoma Perform on International Validation?

BACKGROUND: The Skeletal Oncology Research Group (SORG) machine learning algorithm for predicting survival in patients with chondrosarcoma was develop...

Use of artificial intelligence and machine learning for estimating malignancy risk of thyroid nodules.

PURPOSE OF REVIEW: Current methods for thyroid nodule risk stratification are subjective, and artificial intelligence algorithms have been used to ove...

Knowledge-Based Planning for Intact Cervical Cancer.

Cervical cancer radiotherapy is often complicated by significant variability in the quality and consistency of treatment plans. Knowledge-based planni...

Artificial intelligence and radiomics for radiation oncology.

Artificial intelligence in gastric cancer: Application and future perspectives.

Gastric cancer is the fourth leading cause of cancer-related mortality across the globe, with a 5-year survival rate of less than 40%. In recent years...

Can computers conceive the complexity of cancer to cure it? Using artificial intelligence technology in cancer modelling and drug discovery.

Drug discovery and the development of safe and effective therapeutics is an intricate procedure, further complicated in the context of cancer research...

Brain tumor classification in MRI image using convolutional neural network.

Brain tumor is a severe cancer disease caused by uncontrollable and abnormal partitioning of cells. Recent progress in the field of deep learning has ...

Automatic sleep staging using heart rate variability, body movements, and recurrent neural networks in a sleep disordered population.

STUDY OBJECTIVES: To validate a previously developed sleep staging algorithm using heart rate variability (HRV) and body movements in an independent b...

Predicting Individual Remission After Electroconvulsive Therapy Based on Structural Magnetic Resonance Imaging: A Machine Learning Approach.

OBJECTIVE: To identify important clinical or imaging features predictive of an individual's response to electroconvulsive therapy (ECT) by utilizing a...

Deep learning assisted differentiation of hepatocellular carcinoma from focal liver lesions: choice of four-phase and three-phase CT imaging protocol.

PURPOSE: To evaluate whether a three-phase dynamic contrast-enhanced CT protocol, when combined with a deep learning model, has similar accuracy in di...

[Artificial intelligence and smartphone program applications (Apps) : Relevance for dermatological practice].

ADVANTAGES OF ARTIFICIAL INTELLIGENCE (AI): With responsible, safe and successful use of artificial intelligence (AI), possible advantages in the fiel...

Assessing the Anti-cancer Therapeutic Mechanism of a Herbal Combination for Breast Cancer on System-level by a Network Pharmacological Approach.

BACKGROUND/AIM: Accumulating evidence has shown therapeutic effects of herbals on breast cancer, a commonly diagnosed malignancy in women worldwide. H...

Machine Learning in Oncology: What Should Clinicians Know?

The volume and complexity of scientific and clinical data in oncology have grown markedly over recent years, including but not limited to the realms o...

Deep Convolutional Neural Networks for Thyroid Tumor Grading using Ultrasound B-mode Images.

The performances of deep convolutional neural network (DCNN) modeling and transfer learning (TF) for thyroid tumor grading using ultrasound imaging we...