AIMC Topic: Male

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Predicting the first smoking lapse during a quit attempt: A machine learning approach.

Drug and alcohol dependence
BACKGROUND: Just-in-time adaptive interventions (JITAI) aim to prevent smoking lapse using tailored support delivered via mobile technology in the moments when it is most needed. Effective smoking cessation JITAI rely on the development of accurate d...

Machine learning from wristband sensor data for wearable, noninvasive seizure forecasting.

Epilepsia
OBJECTIVE: Seizure forecasting may provide patients with timely warnings to adapt their daily activities and help clinicians deliver more objective, personalized treatments. Although recent work has convincingly demonstrated that seizure risk assessm...

Evidence-based evolution of our robot-assisted laparoscopic prostatectomy (RALP) technique through 13,000 cases.

Journal of robotic surgery
Robot-assisted laparoscopic radical prostatectomy (RALP) has become the standard of surgical care in the USA and around the world. Over the past 18 years, we have performed 13,000 radical prostatectomies, and our surgical technique has evolved over t...

Application of Computed Tomography Imaging in Diagnosis of Endocrine Nerve of Gastric Cancer and Nursing Intervention Effect.

World neurosurgery
In this article, some parameters and characteristics of computed tomography (CT) images in patients with gastric cancer are analyzed and the application of CT images in the diagnosis of gastric cancer endocrine nerves and the impact of nursing interv...

Personalized treatment for coronary artery disease patients: a machine learning approach.

Health care management science
Current clinical practice guidelines for managing Coronary Artery Disease (CAD) account for general cardiovascular risk factors. However, they do not present a framework that considers personalized patient-specific characteristics. Using the electron...

Machine learning and individual variability in electric field characteristics predict tDCS treatment response.

Brain stimulation
BACKGROUND: Transcranial direct current stimulation (tDCS) is widely investigated as a therapeutic tool to enhance cognitive function in older adults with and without neurodegenerative disease. Prior research demonstrates that electric current delive...

A peripheral inflammatory signature discriminates bipolar from unipolar depression: A machine learning approach.

Progress in neuro-psychopharmacology & biological psychiatry
BACKGROUND: Mood disorders (major depressive disorder, MDD, and bipolar disorder, BD) are considered leading causes of life-long disability worldwide, where high rates of no response to treatment or relapse and delays in receiving a proper diagnosis ...

Myoelectric digit action decoding with multi-output, multi-class classification: an offline analysis.

Scientific reports
The ultimate goal of machine learning-based myoelectric control is simultaneous and independent control of multiple degrees of freedom (DOFs), including wrist and digit artificial joints. For prosthetic finger control, regression-based methods are ty...