Smartphone App for Improving Self-Awareness of Adherence to Edoxaban Treatment in Patients With Atrial Fibrillation (ADHERE-App Trial): Randomized Controlled Trial.

Background: Adherence to oral anticoagulant therapy is essential to prevent ischemic stroke in patients with atrial fibrillation (AF).

Objective: This study aimed to evaluate whether smartphone app-based interventions improve medication adherence in patients with AF.

Methods: This open-label, multicenter randomized controlled trial (ADHERE-App [Self-Awareness of Drug Adherence to Edoxaban Using an Automatic App Feedback System] study) enrolled patients with AF treated with edoxaban for stroke prevention.

Application and Potential of Artificial Intelligence in Heart Failure: Past, Present, and Future.

The prevalence of heart failure (HF) is increasing, necessitating accurate diagnosis and tailored treatment. The accumulation of clinical information from patients with HF generates big data, which poses challenges for traditional analytical methods. To address this, big data approaches and artificial intelligence (AI) have been developed that can effectively predict future observations and outcomes, enabling precise diagnoses and personalized treatments of patients with HF.

Central pancreatectomy: A viable option for solid pseudopapillary neoplasm - A case report.

Introduction: Solid pseudopapillary neoplasms (SPNs) of the pancreas are rare tumors, comprising about 1 % of pancreatic tumors. They primarily affect females during their reproductive phase and have a favorable prognosis. SPNs are usually asymptomatic or present with mild symptoms.

From Recurrent Pain to a Life-Threatening Condition: A Case Report of Left Paraduodenal Hernia.

Paraduodenal hernia (PDH) is the most frequent type of congenital hernia, especially on the left side. Although acute intestinal obstruction due to internal hernias is rare, it can be life-threatening if not detected and treated promptly. Here, we present the case of a 36-year-old man who presented to the emergency department with an acute intestinal obstruction that had been developing for three days.

Primary Closure vs T-Tube Drainage Following Open Choledochotomy for CBD (Common Bile Duct) Stones.

Background: Choledocholithiasis affects 10%-15% of individuals with gallbladder stones. Approximately 7%-15% of cholecystectomy patients develop common bile duct (CBD) stones. It occurs more frequently in older age groups.

Endodermal sinus tumor with pancreatic origin: A case report.

Endodermal Sinus tumor is a rare malignant type of germ cell tumor (GCT). Primary endodermal sinus tumor, especially in the head of pancreas, is extremely rare. The case under consideration is of a 22 year old male who presented with pancreatic mass causing postprandial nausea and vomiting, and raised AFP levels.

Rationale design and efficacy of a smartphone application for improving self-awareness of adherence to edoxaban treatment: study protocol for a randomised controlled trial (adhere app).

Introduction: High adherence to oral anticoagulants is essential for stroke prevention in patients with atrial fibrillation (AF). We developed a smartphone application (app) that pushes alarms for taking medication and measuring blood pressure (BP) and heart rate (HR) at certain times of the day. In addition to drug alarms, the habit of measuring one's BP and HR may reinforce drug adherence by improving self-awareness of the disease.

A practical approach towards causality mining in clinical text using active transfer learning.

Objective: Causality mining is an active research area, which requires the application of state-of-the-art natural language processing techniques. In the healthcare domain, medical experts create clinical text to overcome the limitation of well-defined and schema driven information systems. The objective of this research work is to create a framework, which can convert clinical text into causal knowledge.

An Empirical Method of Automatic Pattern Extraction for Clinical Text Classification.

Clinical text classification is an indispensable and extensively studied problem in medical text processing. Existing research primarily employs machine learning and pattern based approaches to address the stated problem. In general, pattern based approaches perform better than other methods.

Cognitive disturbance comparison among drug-naïve depressed cases and healthy controls.

Objective: To assess and compare cognitive disturbances among newly diagnosed depressed and healthy control cases on the McNair and Kahn auto-evaluation scale.

Study Design: Comparative, cross-sectional study.

Place And Duration Of Study: Out-patients Department of Psychiatry, Jinnah Postgraduate Medical Centre, Karachi, Pakistan, from February to May, 2007.

Psychiatric disorders in bone marrow transplant patients.

Objective: To identify the psychiatric illnesses in patients with hematological/oncological disorders encountered during blood and bone marrow transplantation.

Design: Cross-sectional study.

Place And Duration Of Study: Bismillah Taqee Institute of Health Sciences and Blood Diseases Centre, Karachi from December 2002 to December 2005.

Clinical features of depressive disorder among patients below 18 years of age.

Objective: To determine clinical manifestations of depressive disorder among cases below 18 years.

Design: Cross-sectional study.

Place And Duration Of Study: Carried out at NMI (Neurospinal Medical Institute), Karachi, over a period of 3 years (October 2001 to 2004).