Datasets:

hetanshwaghela
/

autoscientist-healthcare-reasoning

prompt stringlengths 32 7.04k	completion stringlengths 20 24.8k
Analyze the following clinical case to identify the specific vitamin deficiency described. Clinical Presentation: - Patient: 10-year-old boy - Dermatological Symptoms: Severe sunburns that do not heal; an erythematous (red), scaling rash. - Neurological Symptoms: Wide stance gait (ataxia) and instabili...	### Clinical Reasoning: Vitamin Deficiency Identification Based on the clinical presentation and the specified genetic etiology, the specific vitamin deficiency contributing to this condition is Niacin (Vitamin B3). The following analysis details the clinical reasoning linking the observed symptoms to this defic...
### Clinical Case Analysis Patient Profile - Demographics: 50-year-old Caucasian man - Presentation: Admitted to the ER with intense abdominal pain radiating to the back, nausea, and vomiting. - Vitals: Hypotension (low blood pressure) and tachycardia (rapid heart rate). - Labs: Elevated serum lipa...	### Clinical Reasoning and Analysis 1. Establishment of Primary Diagnosis and Severity The initial presentation is classic for Acute Pancreatitis, supported by two of the standard diagnostic criteria: characteristic intense abdominal pain radiating to the back, and elevated serum lipase and amylase levels. The...
# Logic Puzzle: White Elephant Gift Exchange ## Scenario Alice, Bob, and Claire are participating in a white elephant gift exchange. At the start of the event, each person holds a present of a different color: - Alice: white present - Bob: blue present - Claire: pink ball ## Sequence of Events As the even...	To determine the final distribution of gifts in this sequential exchange problem, we must model the system as a series of discrete state transitions. In combinatorics and permutation theory, such problems are best solved by tracking the position of each element (in this case, the specific gifts) through a defined seque...
You are an expert in obstetrics and gynecology. Analyze the following clinical scenario and identify the method that is NOT generally preferred for Medical Termination of Pregnancy (MTP). Clinical Scenario: A 28-year-old woman, whose ultrasound at 13 weeks reveals the fetus has anencephaly, is seeking medical term...	### Clinical Analysis and Method Selection for Termination of Pregnancy at 13 Weeks Clinical Assessment The patient is at 13 weeks of gestation, placing the pregnancy at the transition into the early second trimester. The diagnosis of fetal anencephaly—a lethal neural tube defect incompatible with life—is a recogn...
Calculate the dimensions of the resulting matrix from the multiplication of Matrix A (dimensions 2 × 7) and Matrix B (dimensions 7 × 5). Note: In matrix multiplication, if an m × n matrix is multiplied by an n × p matrix, the resulting matrix has dimensions m × p.	To determine the dimensions of the resulting matrix from the multiplication of Matrix A and Matrix B, we must apply the fundamental rules of linear algebra regarding matrix conformability and dimensional analysis. This process ensures that the operation is mathematically valid and allows us to predict the structure of ...
### Clinical Case Analysis Patient Profile: - Age/Sex: 76-year-old woman - Presenting Symptoms: New-onset syncope and early fatigue on exertion - Physical Exam Findings: Systolic ejection murmur at the right sternal border radiating to the carotids Task: Based on the clinical presentation describe...	### Characteristic Arterial Pulse Finding Based on the clinical presentation of a 76-year-old woman with new-onset syncope, exertional fatigue, and a systolic ejection murmur at the right sternal border radiating to the carotids, the specific arterial pulse finding typically associated with aortic stenosis is **pulsus...
# Clinical Case Analysis: Ocular Symptoms and Systemic Findings ## Patient Profile - Age/Sex: 46-year-old woman - Presenting Complaint: Persistent right eye irritation (itching and redness) for the past 6 months. - Medical History: Hypertension, hyperlipidemia, aggressive tooth decay, and a smoking habit. ...	### Clinical Reasoning and Analysis The presentation of this 46-year-old woman involves a constellation of findings that strongly points toward a systemic autoimmune etiology manifesting with ocular surface disease. The core features include chronic ocular irritation (6 months duration), objective evidence of aqueous ...
# Optimization Problem: Minimizing Cylinder Manufacturing Cost ## Objective Determine the dimensions (radius and height) of a cylindrical container that minimize the total manufacturing cost, given specific volume and material cost constraints. ## Given Parameters - Target Volume: 10 cubic feet - **Top and Bottom...	### Optimization of Cylindrical Container Manufacturing Cost This problem addresses a classic constrained optimization scenario frequently encountered in industrial design and manufacturing engineering. The objective is to determine the geometric dimensions of a cylindrical container that minimize total production cos...
Answer the following medical question regarding wound healing timelines: At what time interval after a traumatic laceration are activated fibroblasts, myofibroblasts, and capillary sprouts most abundant in the wound of a 29-year-old carpenter? Requirements: 1. Identify the specific phase of wound healing described (c...	### Wound Healing Phase and Timeline Analysis Based on established principles of wound healing physiology and histopathology, the cellular components described—activated fibroblasts, myofibroblasts, and capillary sprouts—are the defining hallmarks of the Proliferative Phase of wound healing. In a standard, uncompl...
Calculate the total annual dividend income for Mr. Torres based on the following details: - Shares Owned: 350 shares of Krescostock - Quarterly Dividend: $1.20 per share (paid 4 times per year) - Year-End Dividend: $0.30 per share (paid once per year) Provide the step-by-step calculation and the final tot...	To determine Mr. Torres's total annual dividend income from his holdings in Krescostock, we must break down the payment structure into its two distinct components: the recurring quarterly distributions and the supplemental year-end distribution. Understanding how these payments aggregate is fundamental to projecting ca...
Sort the following list of words alphabetically: murk pvc singlet yeats muslim coachmen clergymen companion gazpacho embark pristine granular hobble fatten allot too niggle chauncey threefold coddington	To arrange the provided list of words into a precise alphabetical sequence, one must apply strict lexicographical rules, evaluating each term character by character from left to right. This process ensures that every entry finds its exact position relative to others sharing similar initial letters, a method essential f...
### Clinical Case Analysis Patient Profile: - Demographics: 25-year-old woman - Presenting Symptoms: Weight gain, oligomenorrhea (infrequent menstrual periods), and amenorrhea (absence of menstrual periods) for 8 months. - Vital Signs: Blood pressure of 160/100 mm Hg. Clinical Question: Based on t...	### Clinical Case Analysis and Diagnostic Reasoning #### 1. Immediate Clinical Assessment and Safety Considerations The presentation of a 25-year-old woman with a blood pressure of 160/100 mm Hg is a significant clinical finding. In a patient of this age, this reading classifies as Stage 2 Hypertension and strongly su...
A surgeon excises a portion of the liver located to the left of the attachment of the falciform ligament. Based on the Couinaud classification of liver segments, identify which segments have been resected from the options below: A. Segment 1a and 4 B. Segment 1 and 4b C. Segment 2 and 3 D. Segment 1 and 3	### Conclusion Based on the Couinaud classification of liver segments and the anatomical landmark provided, the correct option is C. Segment 2 and 3. ### Anatomical Reasoning and Segment Identification To determine the correct segments, we must apply the principles of the Couinaud classification system, which divi...
# Clinical Case Analysis: Diabetes, Renal Failure, and Vitamin D Metabolism Analyze the following clinical scenario to determine the correct diagnosis and associated serum calcium level. ## Patient Profile - Age/Sex: 55-year-old man - History: Long-standing diabetes mellitus - Presentation: Fragility frac...	### Clinical Case Analysis: Diabetes, Renal Failure, and Vitamin D Metabolism This case illustrates the classic pathophysiology of Chronic Kidney Disease-Mineral and Bone Disorder (CKD-MBD). To determine the correct diagnosis and expected serum calcium level, we must systematically analyze the interplay between renal ...
# Clinical Case Analysis: Most Likely Diagnosis ## Patient Profile & History Analyze the following clinical scenario to determine the most likely diagnosis: - Patient: 56-year-old woman. - Presenting Symptoms: Sleep disturbances and sadness. - Onset: Symptoms began one month ago, immediately following her...	### Clinical Case Analysis: Most Likely Diagnosis Based on the clinical presentation, history, and behavioral observations provided, the most likely diagnosis is Normal Bereavement (Uncomplicated Grief). While the patient exhibits symptoms that overlap with depressive disorders—such as sadness, sleep disturbance...
### Clinical Case Analysis Patient Profile * Demographics: 32-year-old man * History: Asthma, significant smoking history * Presentation: Severe respiratory distress with minimal air movement on physical exam * Current Status: Refractory to initial treatment (Albuterol, Magnesium Sulfate, T...	### Clinical Reasoning and Analysis Emergency Status Flag This clinical scenario represents a life-threatening medical emergency. The patient is exhibiting signs of impending respiratory arrest. Immediate intervention is required to prevent cardiopulmonary collapse. This analysis is for educational purposes; i...
# Medical Case Analysis: Subhepatic Fluid Accumulation ## Clinical Scenario A 32-year-old man was readmitted to the hospital with abdominal pain and sepsis after a laparotomy for trauma. A CT scan revealed fluid accumulation in the subhepatic space. ## Question Which organ, when injured, is most likely to cause direc...	# Medical Case Analysis: Subhepatic Fluid Accumulation ## 1. Identification of the Organ The organ most anatomically linked to the subhepatic space that, when injured, is most likely to cause direct fluid accumulation and delayed sepsis following trauma laparotomy is the duodenum (specifically the first and second...
Analyze the following multiple-choice question regarding Stephan's Curve and dental caries: Which of the following factors in the stephan's curve is related to the caries incidence and sugar intake: A. Physical form of sugar B. Frequency of sugar intake C. Ph of plaque D. Quantity of sugar intake Task: 1. Identify th...	### Analysis of Stephan's Curve and Caries Incidence Correct Option: B. Frequency of sugar intake #### Detailed Explanation and Clinical Reasoning The relationship between dietary sugars and dental caries is fundamentally governed by the dynamics of the oral biofilm (plaque) environment, a phenomenon classic...
### Clinical Scenario Analysis Patient Profile: - Diagnosis: Acute Myeloid Leukemia (AML) - Current Status: Post-induction chemotherapy - Complication: Leukopenia (abnormally low white blood cell count) - Clinical Signs: No signs of infection; stable vital signs Task: Based on the profile abov...	### Clinical Reasoning and Prophylactic Recommendation Based on the clinical profile provided—specifically a patient with Acute Myeloid Leukemia (AML) status post-induction chemotherapy presenting with leukopenia (neutropenia) but remaining afebrile and hemodynamically stable—the following analysis outlines the standa...
Complete the provided sequence by adding the necessary characters to ensure all parentheses, brackets, and braces are properly closed and balanced. Input: < { < ( )	To resolve the sequence `< { < ( )` and ensure all delimiters are properly closed and balanced, we must apply the fundamental principles of nested structural validation. This process treats the input as a Last-In, First-Out (LIFO) stack, where every opening symbol must be matched by a corresponding closing symbol in th...
# Medical Knowledge Assessment ## Context Canagliflozin is a medication used to treat type 2 diabetes mellitus. Before initiating this therapy, it is critical to evaluate the patient's kidney function to ensure safety and appropriate dosing. ## Task Identify the specific laboratory parameter that must be evaluated to...	### Clinical Reasoning and Laboratory Evaluation for Canagliflozin Initiation The initiation of canagliflozin, a sodium-glucose cotransporter 2 (SGLT2) inhibitor, requires a rigorous assessment of renal physiology to ensure therapeutic efficacy and patient safety. The mechanism of action for this class of medications ...
### Clinical Case Analysis Patient Presentation: A 46-year-old woman presents with 2 days of intermittent abdominal pain and vomiting, along with a history of upper abdominal pain radiating to her scapulae over the past 3 months, which improved with ibuprofen. She has a fever, tachycardia, and diffuse tenderness o...	### Clinical Case Analysis Most Likely Diagnosis: Gallstone Ileus Clinical Reasoning and Pathophysiology The clinical presentation is highly characteristic of gallstone ileus, a mechanical bowel obstruction caused by the migration of a large gallstone through a cholecystenteric fistula. This condition represe...
# Medical Case Analysis: Pediatric Nephrotic Syndrome ## Instructions Analyze the clinical vignette provided below. Based on the patient's presentation and diagnostic findings, identify the specific hemodynamic factor responsible for the expected increase in glomerular filtration rate (GFR). Select the single best ans...	### Clinical Case Analysis and Pathophysiological Reasoning #### 1. Clinical Presentation and Diagnosis The clinical vignette describes a 9-year-old boy presenting with the classic features of nephrotic syndrome: rapid onset of facial swelling and pitting edema of the lower limbs, foamy urine, and 4+ proteinuria o...
### Medical Case Analysis Patient Profile: - Age: 2 years old - History: Accidental ingestion of kerosene Clinical Presentation: - Symptoms: Cough, dyspnea (difficulty breathing), and high fever. - Radiological Findings: Chest radiograph shows ill-defined patchy opacities. Question: Based on the clinical...	### Clinical Reasoning and Case Analysis 1. Pathophysiological Connection: Kerosene Ingestion and Respiratory Symptoms The clinical presentation of a 2-year-old with a history of accidental kerosene ingestion followed by cough, dyspnea, and fever is a classic depiction of hydrocarbon aspiration pneumonitis. Kerose...
Identify the bacterial species most commonly responsible for prosthetic valvular heart disease (an infection of an artificial heart valve) when the onset occurs within two months of surgery.	### Identification of the Predominant Pathogen In the clinical classification of prosthetic valve endocarditis (PVE), the timing of onset is a critical determinant in identifying the most likely causative organism. When infection occurs within two months of surgery (early-onset PVE), the etiology is typically linked t...
# Clinical Case Analysis: Flail Chest Management ## Patient Scenario Analyze the following clinical presentation: - Patient: 35-year-old man - Incident: Car accident - Injuries: Multiple rib fractures resulting in paradoxical chest movement (flail chest) - Diagnostic Findings: Chest X-ray shows no pneu...	# Clinical Case Analysis: Flail Chest Management ## 1. Primary Clinical Priority In the setting of a flail chest with stable vital signs and no immediate evidence of pneumothorax or hemothorax on initial imaging, the primary clinical priority is **aggressive multimodal pain management combined with rigorous pulmonary ...
In the context of kidney stone formation (the process where solid masses form in the kidney from crystals in the urine), identify which condition is least likely to lead to the formation of a calcium-containing kidney stone (a stone composed primarily of calcium oxalate or calcium phosphate).	### Clinical Reasoning Regarding Calcium-Containing Nephrolithiasis To determine which condition is least likely to lead to the formation of a calcium-containing kidney stone (specifically calcium oxalate or calcium phosphate), it is essential to analyze the biochemical environment of the urinary tract and the pathoph...
Identify the specific enzyme within the mitochondrial electron transport chain (ETC) that does not contribute to the generation of the proton gradient (electrochemical potential) across the inner mitochondrial membrane. Provide the name of the enzyme and a brief explanation of its function relative to proton pumping.	### The Enzyme That Does Not Pump Protons: Succinate Dehydrogenase (Complex II) Within the mitochondrial electron transport chain (ETC), the specific enzyme complex that facilitates electron transfer without contributing directly to the generation of the proton gradient across the inner mitochondrial membrane is **Suc...
Analyze the legal reasoning behind the conclusion that an employee's act of saving their boss's life does not create an enforceable promise of lifetime employment. In your response: 1. Identify the Core Legal Principle: Explain the doctrine of consideration and why past acts (past consideration) generally fail to ...	### Legal Analysis of Enforceability in Employment Promises Based on Past Acts The question of whether an employee's heroic act, such as saving an employer's life, creates an enforceable promise of lifetime employment centers on the fundamental requirements of contract formation. While the moral weight of such an act ...
Analyze the following SVG path element to determine which geometric shape it draws from the provided options. SVG Path Data: <path d="M 40.99,29.44 L 35.53,38.54 L 29.62,35.00 M 29.62,35.00 L 35.07,25.90 L 32.79,24.53 L 43.98,18.25 L 43.26,30.80 L 40.99,29.44"/> Options: (A) circle (B) heptagon (C) hexagon (D) kite (...	To determine the geometric shape represented by the provided SVG path element, we must systematically parse the path data string, extract the coordinate vertices, and evaluate the topological structure of the resulting figure. ### 1. Parsing the SVG Path Data The `d` attribute contains the drawing commands: `d="M 40....
# Engineering Calculation: Bolt Diameter for Cast-Iron Flanged Coupling ## Objective Calculate the required bolt diameter for a flanged coupling system based on the provided mechanical specifications and design constraints. ## System Specifications - Shaft Material: Steel - Coupling Material: Cast-iron flange...	# Engineering Calculation: Bolt Diameter for Cast-Iron Flanged Coupling The following analysis determines the minimum required bolt diameter for the specified flanged coupling system. The calculation proceeds through unit normalization, force derivation, stress analysis, and geometric determination, adhering to standa...

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🩺 Adapted Healthcare Clinical-Reasoning (AutoScientist)

Built with Adaptive Data by Adaption. A grounded, safety-blueprinted clinical-reasoning dataset — and a rigorous, fully-reproducible study of when data adaptation helps a small model, and when it doesn't.

📈 Adaptive Data quality	Before → After
Overall quality score	7.0 → 9.1 (+30%)
Quality grade	B → A
Completion quality	+37.9%
Message quality	+17.6%
Percentile vs. reference corpus	15.3 → 33.0

20,000 rows of English reason-then-answer clinical reasoning across specialties (cardiology, oncology, endocrinology, infectious disease, psychiatry, and more), grounded under an explicit clinical-safety blueprint and blended with curated public-health operations examples.

✨ Why this dataset

Most "medical LLM" datasets optimize for a final answer. This one optimizes for the reasoning that earns the answer — and for doing it safely: grounded in evidence, hedged appropriately, escalating red flags, and refusing when uncertain. Every row is prompt → step-by-step reasoning → justified conclusion, then hardened with Adaptive Data's hallucination_mitigation under a clinical blueprint.

The result is a +30% platform-measured quality lift (Grade B→A) with the largest gain exactly where it matters clinically — completion quality +37.9%.

🔬 Provenance pipeline (reproducible end-to-end)

FreedomIntelligence/medical-o1-reasoning-SFT   (Apache-2.0, gold chain-of-thought)
        │   prompt = Question
        │   completion = Complex_CoT + "\n\nFinal answer:\n" + Response
        ▼
+ 30 curated CDC-grounded public-health operations rows   (safe escalation / refusal / grounding)
        ▼
Adaptive Data by Adaption   →   deduplication + hallucination_mitigation
        │   steered by a clinical-reasoning safety blueprint
        ▼
Adapted dataset (20,000 rows)   ──►   AutoScientist training (Qwen3.5-0.8B, LoRA)

Dataset id: 26048b57-f164-46d5-810b-12d498a76660
Clinical safety blueprint: ground in evidence; never fabricate stats / dosages / citations; preserve numbers exactly; present as educational reasoning, not diagnosis; recommend clinician confirmation; flag emergencies; state uncertainty.

🧬 Data fields

Field	Type	Description
`prompt`	string	The clinical question / case / instruction.
`completion`	string	Step-by-step reasoning followed by a justified conclusion.

📦 Splits

train — 20,000 rows (avg completion ≈ 780 words).
A small held-out private evaluation set (public-health operations, source- and scenario-disjoint) is kept off-platform and not released, to prevent leakage.

🧪 The honest science: what we learned training on it

We trained the companion Qwen/Qwen3.5-0.8B (LoRA) on this data and evaluated it head-to-head against its base with an LLM judge (Gemini 3.1 pro, 200 held-out samples). The base model won (58/42). We didn't stop there — we ran a second, larger run (60k rows, +40% general-purpose data, tuned recipe) and it landed lower (62/38).

Two clean runs, one conclusion — a reproducible finding, not a fluke:

Supervised fine-tuning a 0.8B already-instruction-tuned model on long (≈780-word) chain-of-thought increases verbosity, and the judge prefers the base's crisper answers. Dataset quality (+30%) and small-model head-to-head win-rate are different axes — a better dataset does not automatically beat a strong small base.

Evidence (see the model card): eval-loss plateaued after ~epoch 1 while train-loss kept falling (overfitting), and a higher-LR / more-steps recipe moved further from base and lost by more.

This is exactly the kind of result the AutoScientist framing is built to surface: the dataset is the contribution; the model is the honestly-reported experiment.

✅ Intended use

Fine-tuning / evaluating assistants for grounded clinical reasoning and public-health operations guidance.
Research on chain-of-thought, hallucination mitigation, grounding, refusal, and the dataset-quality-vs-small-model-capability question above.

⚠️ Out-of-scope, limitations & safety

Educational decision-support, not a medical device. Not for individual diagnosis, treatment, or medication dosing without a qualified clinician.
Reasoning is partly machine-generated (GPT-4o + medical verifier upstream, then Adaptive Data); residual errors possible. English, exam-style skew.
Guidance can become superseded; defer to current official sources.
Present conclusions as reasoning to be confirmed; never fabricate stats/dosages/ citations; preserve numeric values exactly; escalate emergencies.

📜 Source, attribution & licensing

Foundation: FreedomIntelligence/medical-o1-reasoning-SFT — Apache-2.0 (redistribution permitted with attribution). This adapted derivative: Apache-2.0.
Public-health blend: U.S. federal public-domain text. Source: Centers for Disease Control and Prevention. No CDC endorsement is implied.
Adapted with Adaptive Data by Adaption.

🔗 Companion artifacts

🧪 Live demo (HF Space): https://huggingface.co/spaces/hetanshwaghela/autoscientist-healthcare-demo
Model (LoRA): https://huggingface.co/hetanshwaghela/autoscientist-healthcare-reasoning
Kaggle dataset: https://www.kaggle.com/datasets/hetanshwaghela1/autoscientist-healthcare-reasoning
Kaggle model: https://www.kaggle.com/models/hetanshwaghela1/autoscientist-healthcare-reasoning

Built with Adaptive Data by Adaption. Foundation: FreedomIntelligence/medical-o1-reasoning-SFT (Apache-2.0). Public-health blend: CDC public-domain text.