AIMC Topic: Precision Medicine

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The coming 15 years in gynaecological pathology: digitisation, artificial intelligence, and new technologies.

Histopathology
Surgical pathology forms the cornerstone of modern oncological medicine, owing to the wealth of clinically relevant information that can be obtained from tissue morphology. Although several ancillary testing modalities have been added to surgical pat...

Personalized prognostic prediction of treatment outcome for depressed patients in a naturalistic psychiatric hospital setting: A comparison of machine learning approaches.

Journal of consulting and clinical psychology
OBJECTIVE: Research on predictors of treatment outcome in depression has largely derived from randomized clinical trials involving strict standardization of treatments, stringent patient exclusion criteria, and careful selection and supervision of st...

Quadruple Decision Making for Parkinson's Disease Patients: Combining Expert Opinion, Patient Preferences, Scientific Evidence, and Big Data Approaches to Reach Precision Medicine.

Journal of Parkinson's disease
Clinical decision making for Parkinson's disease patients is supported by a combination of three distinct information resources: best available scientific evidence, professional expertise, and the personal needs and preferences of patients. All three...

A Deep Learning Framework for Predicting Response to Therapy in Cancer.

Cell reports
A major challenge in cancer treatment is predicting clinical response to anti-cancer drugs on a personalized basis. Using a pharmacogenomics database of 1,001 cancer cell lines, we trained deep neural networks for prediction of drug response and asse...

Artificial intelligence in the diagnosis of cardiovascular disease.

Revista da Associacao Medica Brasileira (1992)
Artificial intelligence (AI) is a field of computer science that aims to mimic human thought processes. AI techniques have been applied in cardiovascular medicine to explore novel genotypes and phenotypes in existing diseases, improve the quality of ...

Application of preoperative artificial neural network based on blood biomarkers and clinicopathological parameters for predicting long-term survival of patients with gastric cancer.

World journal of gastroenterology
BACKGROUND: Because of the powerful abilities of self-learning and handling complex biological information, artificial neural network (ANN) models have been widely applied to disease diagnosis, imaging analysis, and prognosis prediction. However, the...

Deep learning for clustering of multivariate clinical patient trajectories with missing values.

GigaScience
BACKGROUND: Precision medicine requires a stratification of patients by disease presentation that is sufficiently informative to allow for selecting treatments on a per-patient basis. For many diseases, such as neurological disorders, this stratifica...

20th Annual Feigenbaum Lecture: Echocardiography for Precision Medicine-Digital Biopsy to Deconstruct Biology.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
Heart failure with preserved ejection fraction (HFpEF) is a complex, heterogeneous syndrome in need of improved classification given its high morbidity and mortality and few effective treatment options. HFpEF represents an ideal setting to examine th...

Applying machine learning to predict real-world individual treatment effects: insights from a virtual patient cohort.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: We aimed to investigate bias in applying machine learning to predict real-world individual treatment effects.

Of Slide Rules and Stethoscopes: AI and the Future of Doctoring.

The Hastings Center report
Historically, the practice of medicine has been a physically intimate endeavor. Physicians have used their hands to palpate and reveal the secrets hidden within the body. Smelling the breath for the ketosis of diabetes or tasting the skin for the sal...