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Draft a comprehensive differential diagnosis for acute substernal chest pain in a 45-year-old male with hypertension and hyperlipidemia, diaphoresis, exertional onset, and normal initial ECG/troponin; include life-threatening causes first, key distinguishing features, and immediate diagnostic next steps.

Draft a detailed differential diagnosis for new-onset unilateral throbbing headache with visual aura and brief monocular vision loss in a 32-year-old female on oral contraceptives; include red-flag symptoms, stroke/TIA considerations, and recommended initial workup.

Draft an assessment and plan for stage-2 hypertension (BP 162/98) in an obese 52-year-old with suspected obstructive sleep apnea; include ASCVD risk estimate, lifestyle prescriptions, first-line pharmacotherapy with drug/dose/targets, baseline labs/monitoring, and 4–6 week follow-up.

Draft an assessment and plan for type 2 diabetes follow-up with A1c 9.2% on metformin 1,000 mg BID and eGFR 65; compare adding a GLP-1 receptor agonist vs an SGLT2 inhibitor, address weight loss goals, hypoglycemia education, vaccinations, and micro/macrovascular screening.

Draft a history and physical for a patient presenting with chest pain, including HPI using OLDCARTS, pertinent ROS, PMH/meds/allergies, FH/SH, focused cardiac/pulmonary exam, initial labs and imaging orders, prioritized differential, HEART score risk stratification, and early management.

Draft a history and physical for a new patient with progressive exertional dyspnea, orthopnea, and bilateral leg edema; include differential (heart failure, COPD, PE, anemia, renal disease), targeted exam maneuvers, and first-line diagnostics and management.

Draft a progress note for COPD follow-up two weeks after an acute exacerbation treated with prednisone and antibiotics; include symptom trajectory, CAT score (if available), inhaler technique/adherence, oxygen needs, spirometry plan, smoking cessation counseling, and return precautions.

Draft a progress note for post-operative day 2 after total knee arthroplasty; include pain control strategy, DVT prophylaxis, PT/OT milestones, wound status, bowel/urinary function, labs/vitals review, complications screening, and discharge readiness.

Draft a discharge summary for community-acquired pneumonia admission; include admission/discharge dates, presenting symptoms, radiology/labs, pathogen if identified, inpatient therapies and response, discharge medications with durations, pending tests, follow-up appointments, and return precautions.

Draft a discharge summary for myocardial infarction managed with PCI and drug-eluting stent placement; include cath findings, complications, inpatient course, discharge medications (DAPT, statin, beta-blocker, ACEi/ARB), cardiac rehab referral, and follow-up plan.

Draft discharge instructions for a patient hospitalized with acute decompensated heart failure; include daily weights, sodium and fluid restriction amounts, medication list with dosing, signs of worsening heart failure, follow-up appointments, and lab monitoring plan.

Draft discharge instructions for an asthma exacerbation; include controller and reliever regimen, steroid taper schedule, spacer technique, trigger avoidance, a written asthma action plan, return precautions, and follow-up timing.

Draft a patient handout on managing high blood pressure in plain language; explain what BP numbers mean, key lifestyle steps (DASH diet, sodium limits, alcohol moderation), home BP monitoring instructions, medication adherence tips, and when to call the doctor.

Draft a patient handout for type 2 diabetes education in plain language; cover A1c goals, the plate method, physical activity targets, self-monitoring of blood glucose, hypoglycemia signs and the 15-15 rule, foot care basics, and a vaccination checklist.

Draft a summary of the latest CDC and WHO guidelines for managing community-acquired pneumonia in adults, including empiric antibiotic choices, duration of therapy, and follow-up recommendations.

Draft a plain-language overview of the ADA and AACE guidelines for diabetes management, focusing on A1c goals, weight management, and the use of GLP-1 receptor agonists and SGLT2 inhibitors.

Draft a summary of the 2024 USPSTF breast cancer screening recommendations, including updated screening intervals, risk-based approaches, and the role of MRI for high-risk patients.

Draft a concise summary of NCCN guidelines for melanoma management, including staging, surgical margins, adjuvant therapy, and checkpoint inhibitor recommendations.

Draft treatment alternatives for community-acquired MRSA skin infections in patients allergic to sulfa drugs; include oral and IV options, dosing, and duration.

Draft treatment alternatives for patients with type 2 diabetes who are unable to tolerate GLP-1 receptor agonists due to nausea; include medication substitutions and lifestyle recommendations.

Draft a summary of options for treating refractory depression, comparing ketamine infusions, transcranial magnetic stimulation (TMS), and electroconvulsive therapy (ECT).

Draft treatment options for advanced prostate cancer, including hormonal therapy, radiopharmaceuticals, and novel androgen receptor pathway inhibitors.

Draft a summary of recent research on mRNA vaccine technology beyond COVID-19, including applications in oncology and autoimmune disease prevention.

Draft an easy-to-understand overview of long COVID research, summarizing major symptoms, hypothesized mechanisms, and emerging treatment approaches.

Draft a summary of current research on Alzheimer’s disease biomarkers, including amyloid and tau imaging, and discuss how they influence diagnosis and trial design.

Draft an explanation of the interaction between warfarin and antibiotics such as ciprofloxacin or TMP-SMX, including INR effects and management recommendations.

Draft a summary evaluating drug interactions for patients taking Paxlovid and common cardiovascular drugs; include mechanism and recommended dose adjustments.

Draft a summary of the common and serious side effects of semaglutide, including GI intolerance, gallbladder disease, and thyroid-related warnings.

Draft an overview of potential side effects associated with long-term corticosteroid use, including osteoporosis, glucose intolerance, and adrenal suppression.

Draft a summary of essential lab tests to order in suspected acute pancreatitis, including amylase, lipase, liver enzymes, and metabolic panels, with interpretation guidance.

Draft laboratory workup recommendations for suspected hypothyroidism, including TSH, free T4, thyroid antibodies, and when to consider secondary causes.

Draft an explanation of which labs should be monitored in patients receiving methotrexate therapy, including CBC, LFTs, renal function, and frequency of monitoring.

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Research Article: Use of Novel Open-Source Deep Learning Platform for Quantification of Ki- in Neuroendocrine Tumors – Analytical Validation

Date Published: 2023-12-04

Abstract:
Ki- is a widely used biomarker for quantifying cellular proliferation in tumors, including neuroendocrine tumors (NETs). The Ki- index is calculated by dividing the number of Ki- positive cells by the total number of cells evaluated in a tissue sample. A higher Ki- index indicates a higher rate of cellular proliferation and is associated with a more aggressive tumor phenotype. In NETs, Ki- quantification is used to help determine the tumor grade and prognosis as well as to monitor response to treatment. However, it is important to note that Ki- is not specific for NETs and its expression can be influenced by other factors such as the stage of the cell cycle. Therefore, Ki- should be interpreted in the context of other clinical and pathological features. Artificial intelligence (AI) can be used to support the detection and quantification of Ki- in NETs. This can be done using a variety of techniques such as deep learning algorithms, computer vision and image analysis. Deep learning is a type of AI that has shown promise in the diagnosis and prognostication of NETs.– Deep learning (also known as deep structured learning) is a subfield of machine learning based on artificial neural networks (ANNs) in which the statistic models are established from input training data. Deep learning algorithms can be trained on large amounts of medical imaging data to accurately identify and quantify Ki- positive cells in tissue samples using digital pathology images. The use of AI in Ki- detection has the potential to improve the accuracy and consistency of Ki- quantification, as well as reduce inter-observer variability. Additionally, AI can also reduce the time and resources required for manual Ki- quantification, allowing for a faster and more efficient evaluation of large numbers of tissue samples. Deep learning algorithms can also be used to predict patient outcomes and treatment response, by analyzing imaging and clinical data to identify predictive features associated with disease progression and survival. This can enable the development of personalized treatment plans for patients. However, it is important to note that deep learning algorithms in NET analysis are still in the stage of development and require validation. Also, comparison of AI-based Ki- quantification to traditional manual methods is needed to ensure its accuracy and reliability.–

Introduction:
Ki- is a widely used biomarker for quantifying cellular proliferation in tumors, including neuroendocrine tumors (NETs). The Ki- index is calculated by dividing the number of Ki- positive cells by the total number of cells evaluated in a tissue sample. A higher Ki- index indicates a higher rate of cellular proliferation and is associated with a more aggressive tumor phenotype. In NETs, Ki- quantification is used to help determine the tumor grade and prognosis as well as to monitor response to treatment. However,…

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